Discovery and mapping of cloud-based resource modifications

ABSTRACT

A system includes persistent storage configured to store, a mapping of computing resources provided by a remote computing system to a managed network. The system also includes an application that obtains instructions to modify a computing resource provided by the remote computing system and, based on the instructions, generates and transmits, to the remote computing system, a request to modify the computing resource. The application receives, from the remote computing system, a response indicating a modification to the computing resource and selects a discovery pattern configured to verify the modification by obtaining attributes associated therewith. The application obtains, from the remote computing system, the attributes by executing the discovery pattern and determines, based on the attributes, that the modification has been completed according to the instructions. Based on this determination, the application updates the mapping to indicate the modification and stores, in the persistent storage, the mapping as updated.

BACKGROUND

Computing devices, software applications, storage structures, and othercomputing resources that make up a computer network may be discoveredand the relationships therebetween may be mapped. These elements of thecomputer network, as well as the relationships, may be stored asconfiguration items in a database. The stored configuration items maylater be retrieved and used to generate a visualization of a state orarrangement of these elements within the computer network. Discoveringcomputing resource involves developing software processes that arecapable of gathering the information needed for detection,classification, and/or identification of these computing resources.

SUMMARY

A remote computing system may be configured to provide computingresources on behalf of a managed computer network. These computingresources may include virtual computing devices, load balancers, andstorage volumes distributed across one or more availability zones (e.g.,datacenters) disposed within one or more geographic regions. These andother computing resources may collectively define a cloud-basedcomputing environment that the managed network can use to host softwareapplications, store and serve data, and provide other web-based softwareservices.

A discovery application may be configured to discover and map thecomputing resources that make up the service infrastructure by way ofwhich the cloud-based computing environment is provided. The discoveryapplication may be configured to obtain attributes of the computingresources in different regions and availability zones by way ofapplication programming interfaces (APIs) provided by the remotecomputing system. Based on the attributes, the discovery application maybe configured to generate relationships among the computing resourcesand represent these relationships in a map. The map may indicate, forexample, a distribution of virtual computing devices across one or moreavailability zones, storage volumes utilized by the virtual computingdevices, load balancers configured to distribute traffic among thevirtual computing devices, attributes of physical computing hardware bywhich the different resources are executed, and/or operating systemimages utilized by the virtual computing devices, among other aspects.

In some cases, the managed network may utilize multiple different remotecomputing systems, in addition to any on-premises computing devices, toprovide its services. These different remote computing systems may varyin their names for certain computing resources and/or how thesecomputing resources relate to one another, among other possibilities.For example, the different remote computing systems may refer to adatacenter as an “availability zone,” as a “geographic sub-region,” orsimply a “datacenter.”

However, the discovery application may be configured to utilize a commonmodel (or at least a model derived from the common model) to representaspects of each of these different remote computing systems. Namely, thediscovery application may map each computing resource of multipledifferent remote computing systems to corresponding elements of thecommon model. Thus, a “datacenter” provided by a first remote computingsystem may be mapped to the same model component as an “availabilityzone” provided by another remote computing system. Similarly, theattributes available for each computing resource may be indicated by themodel component, regardless of any differences between the specific setof attributes exposed by the remote computing system. Accordingly,multiple different remote computing systems may be mapped and visualizedusing the common model such that the computing resources thereof can beeasily compared across systems.

The discovery application may additionally be used to manage, modify,adjust, and otherwise change the allocated computing resources. Namely,the discovery application may be used to provision additional computingresources, delete or dispose of computing resources, and/or otherwisemodify the attributes and/or relationships of the computing resources.The discovery application may be configured to obtain instructions thatdefine a target modification, generate a request to implement such amodification, and transmit this request to the remote computing system.Accordingly, modification may be made to the infrastructure provided bya particular remote computing system by way of the discovery applicationand without direct interaction with the interfaces provided by theremote computing systems.

Additionally, the discovery application may also be used to verify thatan actual modification carried out by the remote computing systemmatches the target modification. To that end, the discovery applicationmay utilize a subset of the discovery and mapping operations to obtainattributes of the modified computing resource after the modification hasbeen confirmed by the remote computing system. The discovery applicationmay obtain such attributes and, based thereon, determine whether theactual modification matches the target modification. If so, thediscovery application may update the mapping to maintain consistencybetween the mapping and the actual state of the remote computing systeminfrastructure.

Otherwise, the discovery application may be configured to undo or rollback the modification. Alternatively or additionally, the discoveryapplication may be configured to execute a revised modification using amodified request so as to reach the target modification. The targetmodification to the infrastructure may be user-specified, specified bythe discovery application, or specified by another software applicationthat utilizes the computing resources of the remote computing system.Similarly, the match between the target modification and the actualmodification may be evaluated by a user, by the discovery application,and/or the other application.

In either case, the discovery and mapping process may be used tofacilitate modifications to the computing resources of the remotecomputing system. For example, users unfamiliar with managing the remotecomputing system may nevertheless use a graphical representation of themapping (rather than, e.g., a command line interface that usessystem-specific syntax) to intuitively make modifications to the remotecomputing system by interacting with the graphic representation.Similarly, by confirming the modifications through the discoveryprocess, the discovery application provides visual feedback of anymodifications requested by the users. Thus, users may be easily able toundo and correct any undesired or erroneous modifications.

Accordingly, a first example embodiment may involve a computing systemthat includes persistent storage configured to store data on behalf of amanaged network. A remote computing system provides computing resourceson behalf of the managed network. The computing system also includes adiscovery application configured to perform operations. The operationsinclude obtaining a service identifier that allows access to the remotecomputing system. The service identifier is associated with the managednetwork. The operations also include identifying a geographic region ofthe remote computing system that contains the computing resourcesassociated with the service identifier. The operations additionallyinclude identifying, within the geographic region, (i) virtual computingdevices allocated to the managed network and (ii) attributes of thevirtual computing devices. The operations further include identifying,based on the attributes of the virtual computing devices, (i) one ormore load balancers configured to distribute network traffic among thevirtual computing devices and (ii) one or more storage volumes used bythe virtual computing devices. The operations yet further includedetermining a mapping between the virtual computing devices, the one ormore load balancers, and the one or more storage volumes to represent aservice infrastructure of the remote computing system dedicated to themanaged network. The operations yet additionally include storing, in thepersistent storage, the mapping as one or more configuration items.

A second example embodiment may involve obtaining, by a discoveryapplication, a service identifier associated with a managed network thatallows access to a remote computing system that provides computingresources on behalf of the managed network. The second exampleembodiment may also involve identifying, by the discovery application, ageographic region of the remote computing system that contains thecomputing resources associated with the service identifier. The secondexample embodiment may additionally involve identifying, by thediscovery application and within the geographic region, (i) virtualcomputing devices allocated to the managed network and (ii) attributesof the virtual computing devices. The second example embodiment mayfurther involve identifying, by the discovery application and based onthe attributes of the virtual computing devices, (i) one or more loadbalancers configured to distribute network traffic among the virtualcomputing devices and (ii) one or more storage volumes used by thevirtual computing devices. The second example embodiment may yet furtherinvolve determining, by the discovery application, a mapping between thevirtual computing devices, the one or more load balancers, and the oneor more storage volumes to represent a service infrastructure of theremote computing system dedicated to the managed network. The secondexample embodiment may yet additionally involve storing, in persistentstorage configured to store data on behalf of the managed network, themapping as one or more configuration items.

In a third example embodiment, an article of manufacture may include anon-transitory computer-readable medium, having stored thereon programinstructions that, upon execution by a computing system, cause thecomputing system to perform operations in accordance with the firstexample embodiment or the second example embodiment.

In a fourth example embodiment, a computing system may include at leastone processor, as well as memory and program instructions. The programinstructions may be stored in the memory, and upon execution by the atleast one processor, cause the computing system to perform operations inaccordance with the first example embodiment or the second exampleembodiment.

In a fifth example embodiment, a system may include various means forcarrying out each of the operations of the first example embodiment orthe second example embodiment.

A sixth example embodiment may involve a computing system that includespersistent storage configured to store, as one or more configurationitems and on behalf of a managed network, a mapping of computingresources provided by a remote computing system to the managed network.The mapping represents a service infrastructure of the remote computingsystem dedicated to the managed network. The computing system alsoincludes a discovery application configured to perform operations. Theoperations include obtaining instructions to modify a computing resourceprovided by the remote computing system and, based on the instructions,generating and transmitting, to the remote computing system, a requestto modify the computing resource. The operations also include receiving,from the remote computing system, a response indicating a modificationto the computing resource. The operations additionally include selectinga discovery pattern configured to verify the modification to thecomputing resource by obtaining attributes associated therewith andobtaining, from the remote computing system, the attributes associatedwith the computing resource by executing the discovery pattern. Theoperations further include determining, based on the attributesassociated with the computing resource, that the modification to thecomputing resource has been completed according to the instructions. Theoperations yet further include, based on the modification to thecomputing resource having been completed according to the instructions,updating the mapping to indicate the modification and storing, in thepersistent storage, the mapping as updated.

A seventh example embodiment may involve obtaining, by a discoveryapplication, instructions to modify a computing resource of computingresources provided by a remote computing system to a managed network. Amapping of the computing resources is stored as one or moreconfiguration items in persistent storage on behalf of the managednetwork. The mapping represents a service infrastructure of the remotecomputing system dedicated to the managed network. The seventh exampleembodiment may also involve, based on the instructions, generating andtransmitting, by the discovery application and to the remote computingsystem, a request to modify the computing resource. The seventh exampleembodiment may additionally involve receiving, by the discoveryapplication and from the remote computing system, a response indicatinga modification to the computing resource. The seventh example embodimentmay further involve selecting, by the discovery application, a discoverypattern configured to verify the modification to the computing resourceby obtaining attributes associated therewith and obtaining, by thediscovery application and from the remote computing system, theattributes associated with the computing resource by executing thediscovery pattern. The seventh example embodiment may yet additionallyinvolve determining, by the discovery application and based on theattributes associated with the computing resource, that the modificationto the computing resource has been completed according to theinstructions. The seventh example embodiment may yet further involve,based on the modification to the computing resource having beencompleted according to the instructions, updating, by the discoveryapplication, the mapping to indicate the modification and storing, inthe persistent storage, the mapping as updated.

In an eighth example embodiment, an article of manufacture may include anon-transitory computer-readable medium, having stored thereon programinstructions that, upon execution by a computing system, cause thecomputing system to perform operations in accordance with the sixthexample embodiment or the seventh example embodiment.

In a ninth example embodiment, a computing system may include at leastone processor, as well as memory and program instructions. The programinstructions may be stored in the memory, and upon execution by the atleast one processor, cause the computing system to perform operations inaccordance with the sixth example embodiment or the seventh exampleembodiment.

In a tenth example embodiment, a system may include various means forcarrying out each of the operations of the sixth example embodiment orthe seventh example embodiment.

These, as well as other embodiments, aspects, advantages, andalternatives, will become apparent to those of ordinary skill in the artby reading the following detailed description, with reference whereappropriate to the accompanying drawings. Further, this summary andother descriptions and figures provided herein are intended toillustrate embodiments by way of example only and, as such, thatnumerous variations are possible. For instance, structural elements andprocess steps can be rearranged, combined, distributed, eliminated, orotherwise changed, while remaining within the scope of the embodimentsas claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic drawing of a computing device, inaccordance with example embodiments.

FIG. 2 illustrates a schematic drawing of a server device cluster, inaccordance with example embodiments.

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments.

FIG. 4 depicts a communication environment involving a remote networkmanagement architecture, in accordance with example embodiments.

FIG. 5A depicts another communication environment involving a remotenetwork management architecture, in accordance with example embodiments.

FIG. 5B is a flow chart, in accordance with example embodiments.

FIG. 6 illustrates a remote computing system architecture, in accordancewith example embodiments.

FIG. 7 illustrates a configuration management database model, inaccordance with example embodiments.

FIG. 8 is a message diagram, in accordance with example embodiments.

FIGS. 9A, 9B, 9C, and 9D are message diagrams, in accordance withexample embodiments.

FIG. 10 is a flow chart, in accordance with example embodiments.

FIG. 11 is a flow chart, in accordance with example embodiments.

DETAILED DESCRIPTION

Example methods, devices, and systems are described herein. It should beunderstood that the words “example” and “exemplary” are used herein tomean “serving as an example, instance, or illustration.” Any embodimentor feature described herein as being an “example” or “exemplary” is notnecessarily to be construed as preferred or advantageous over otherembodiments or features unless stated as such. Thus, other embodimentscan be utilized and other changes can be made without departing from thescope of the subject matter presented herein.

Accordingly, the example embodiments described herein are not meant tobe limiting. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations. For example, theseparation of features into “client” and “server” components may occurin a number of ways.

Further, unless context suggests otherwise, the features illustrated ineach of the figures may be used in combination with one another. Thus,the figures should be generally viewed as component aspects of one ormore overall embodiments, with the understanding that not allillustrated features are necessary for each embodiment.

Additionally, any enumeration of elements, blocks, or steps in thisspecification or the claims is for purposes of clarity. Thus, suchenumeration should not be interpreted to require or imply that theseelements, blocks, or steps adhere to a particular arrangement or arecarried out in a particular order.

INTRODUCTION

A large enterprise is a complex entity with many interrelatedoperations. Some of these are found across the enterprise, such as humanresources (HR), supply chain, information technology (IT), and finance.However, each enterprise also has its own unique operations that provideessential capabilities and/or create competitive advantages.

To support widely-implemented operations, enterprises typically useoff-the-shelf software applications, such as customer relationshipmanagement (CRM) and human capital management (HCM) packages. However,they may also need custom software applications to meet their own uniquerequirements. A large enterprise often has dozens or hundreds of thesecustom software applications. Nonetheless, the advantages provided bythe embodiments herein are not limited to large enterprises and may beapplicable to an enterprise, or any other type of organization, of anysize.

Many such software applications are developed by individual departmentswithin the enterprise. These range from simple spreadsheets tocustom-built software tools and databases. But the proliferation ofsiloed custom software applications has numerous disadvantages. Itnegatively impacts an enterprise's ability to run and grow itsoperations, innovate, and meet regulatory requirements. The enterprisemay find it difficult to integrate, streamline and enhance itsoperations due to lack of a single system that unifies its subsystemsand data.

To efficiently create custom applications, enterprises would benefitfrom a remotely-hosted application platform that eliminates unnecessarydevelopment complexity. The goal of such a platform would be to reducetime-consuming, repetitive application development tasks so thatsoftware engineers and individuals in other roles can focus ondeveloping unique, high-value features.

In order to achieve this goal, the concept of Application Platform as aService (aPaaS) is introduced, to intelligently automate workflowsthroughout the enterprise. An aPaaS system is hosted remotely from theenterprise, but may access data, applications, and services within theenterprise by way of secure connections. Such an aPaaS system may have anumber of advantageous capabilities and characteristics. Theseadvantages and characteristics may be able to improve the enterprise'soperations and workflow for IT, HR, CRM, customer service, applicationdevelopment, and security.

The aPaaS system may support development and execution ofmodel-view-controller (MVC) applications. MVC applications divide theirfunctionality into three interconnected parts (model, view, andcontroller) in order to isolate representations of information from themanner in which the information is presented to the user, therebyallowing for efficient code reuse and parallel development. Theseapplications may be web-based, and offer create, read, update, delete(CRUD) capabilities. This allows new applications to be built on acommon application infrastructure.

The aPaaS system may support standardized application components, suchas a standardized set of widgets for graphical user interface (GUI)development. In this way, applications built using the aPaaS system havea common look and feel. Other software components and modules may bestandardized as well. In some cases, this look and feel can be brandedor skinned with an enterprise's custom logos and/or color schemes.

The aPaaS system may support the ability to configure the behavior ofapplications using metadata. This allows application behaviors to berapidly adapted to meet specific needs. Such an approach reducesdevelopment time and increases flexibility. Further, the aPaaS systemmay support GUI tools that facilitate metadata creation and management,thus reducing errors in the metadata.

The aPaaS system may support clearly-defined interfaces betweenapplications, so that software developers can avoid unwantedinter-application dependencies. Thus, the aPaaS system may implement aservice layer in which persistent state information and other data arestored.

The aPaaS system may support a rich set of integration features so thatthe applications thereon can interact with legacy applications andthird-party applications. For instance, the aPaaS system may support acustom employee-onboarding system that integrates with legacy HR, IT,and accounting systems.

The aPaaS system may support enterprise-grade security. Furthermore,since the aPaaS system may be remotely hosted, it should also utilizesecurity procedures when it interacts with systems in the enterprise orthird-party networks and services hosted outside of the enterprise. Forexample, the aPaaS system may be configured to share data amongst theenterprise and other parties to detect and identify common securitythreats.

Other features, functionality, and advantages of an aPaaS system mayexist. This description is for purpose of example and is not intended tobe limiting.

As an example of the aPaaS development process, a software developer maybe tasked to create a new application using the aPaaS system. First, thedeveloper may define the data model, which specifies the types of datathat the application uses and the relationships therebetween. Then, viaa GUI of the aPaaS system, the developer enters (e.g., uploads) the datamodel. The aPaaS system automatically creates all of the correspondingdatabase tables, fields, and relationships, which can then be accessedvia an object-oriented services layer.

In addition, the aPaaS system can also build a fully-functional MVCapplication with client-side interfaces and server-side CRUD logic. Thisgenerated application may serve as the basis of further development forthe user. Advantageously, the developer does not have to spend a largeamount of time on basic application functionality. Further, since theapplication may be web-based, it can be accessed from anyInternet-enabled client device. Alternatively or additionally, a localcopy of the application may be able to be accessed, for instance, whenInternet service is not available.

The aPaaS system may also support a rich set of pre-definedfunctionality that can be added to applications. These features includesupport for searching, email, templating, workflow design, reporting,analytics, social media, scripting, mobile-friendly output, andcustomized GUIs.

The following embodiments describe architectural and functional aspectsof example aPaaS systems, as well as the features and advantagesthereof.

II. EXAMPLE COMPUTING DEVICES AND CLOUD-BASED COMPUTING ENVIRONMENTS

FIG. 1 is a simplified block diagram exemplifying a computing device100, illustrating some of the components that could be included in acomputing device arranged to operate in accordance with the embodimentsherein. Computing device 100 could be a client device (e.g., a deviceactively operated by a user), a server device (e.g., a device thatprovides computational services to client devices), or some other typeof computational platform. Some server devices may operate as clientdevices from time to time in order to perform particular operations, andsome client devices may incorporate server features.

In this example, computing device 100 includes processor 102, memory104, network interface 106, and an input/output unit 108, all of whichmay be coupled by a system bus 110 or a similar mechanism. In someembodiments, computing device 100 may include other components and/orperipheral devices (e.g., detachable storage, printers, and so on).

Processor 102 may be one or more of any type of computer processingelement, such as a central processing unit (CPU), a co-processor (e.g.,a mathematics, graphics, or encryption co-processor), a digital signalprocessor (DSP), a network processor, and/or a form of integratedcircuit or controller that performs processor operations. In some cases,processor 102 may be one or more single-core processors. In other cases,processor 102 may be one or more multi-core processors with multipleindependent processing units. Processor 102 may also include registermemory for temporarily storing instructions being executed and relateddata, as well as cache memory for temporarily storing recently-usedinstructions and data.

Memory 104 may be any form of computer-usable memory, including but notlimited to random access memory (RAM), read-only memory (ROM), andnon-volatile memory (e.g., flash memory, hard disk drives, solid statedrives, compact discs (CDs), digital video discs (DVDs), and/or tapestorage). Thus, memory 104 represents both main memory units, as well aslong-term storage. Other types of memory may include biological memory.

Memory 104 may store program instructions and/or data on which programinstructions may operate. By way of example, memory 104 may store theseprogram instructions on a non-transitory, computer-readable medium, suchthat the instructions are executable by processor 102 to carry out anyof the methods, processes, or operations disclosed in this specificationor the accompanying drawings.

As shown in FIG. 1, memory 104 may include firmware 104A, kernel 104B,and/or applications 104C. Firmware 104A may be program code used to bootor otherwise initiate some or all of computing device 100. Kernel 104Bmay be an operating system, including modules for memory management,scheduling and management of processes, input/output, and communication.Kernel 104B may also include device drivers that allow the operatingsystem to communicate with the hardware modules (e.g., memory units,networking interfaces, ports, and busses), of computing device 100.Applications 104C may be one or more user-space software programs, suchas web browsers or email clients, as well as any software libraries usedby these programs. Memory 104 may also store data used by these andother programs and applications.

Network interface 106 may take the form of one or more wirelineinterfaces, such as Ethernet (e.g., Fast Ethernet, Gigabit Ethernet, andso on). Network interface 106 may also support communication over one ormore non-Ethernet media, such as coaxial cables or power lines, or overwide-area media, such as Synchronous Optical Networking (SONET) ordigital subscriber line (DSL) technologies. Network interface 106 mayadditionally take the form of one or more wireless interfaces, such asIEEE 802.11 (Wifi), BLUETOOTH®, global positioning system (GPS), or awide-area wireless interface. However, other forms of physical layerinterfaces and other types of standard or proprietary communicationprotocols may be used over network interface 106. Furthermore, networkinterface 106 may comprise multiple physical interfaces. For instance,some embodiments of computing device 100 may include Ethernet,BLUETOOTH®, and Wifi interfaces.

Input/output unit 108 may facilitate user and peripheral deviceinteraction with computing device 100. Input/output unit 108 may includeone or more types of input devices, such as a keyboard, a mouse, a touchscreen, and so on. Similarly, input/output unit 108 may include one ormore types of output devices, such as a screen, monitor, printer, and/orone or more light emitting diodes (LEDs). Additionally or alternatively,computing device 100 may communicate with other devices using auniversal serial bus (USB) or high-definition multimedia interface(HDMI) port interface, for example.

In some embodiments, one or more computing devices like computing device100 may be deployed to support an aPaaS architecture. The exact physicallocation, connectivity, and configuration of these computing devices maybe unknown and/or unimportant to client devices. Accordingly, thecomputing devices may be referred to as “cloud-based” devices that maybe housed at various remote data center locations.

FIG. 2 depicts a cloud-based server cluster 200 in accordance withexample embodiments. In FIG. 2, operations of a computing device (e.g.,computing device 100) may be distributed between server devices 202,data storage 204, and routers 206, all of which may be connected bylocal cluster network 208. The number of server devices 202, datastorages 204, and routers 206 in server cluster 200 may depend on thecomputing task(s) and/or applications assigned to server cluster 200.

For example, server devices 202 can be configured to perform variouscomputing tasks of computing device 100. Thus, computing tasks can bedistributed among one or more of server devices 202. To the extent thatthese computing tasks can be performed in parallel, such a distributionof tasks may reduce the total time to complete these tasks and return aresult. For purpose of simplicity, both server cluster 200 andindividual server devices 202 may be referred to as a “server device.”This nomenclature should be understood to imply that one or moredistinct server devices, data storage devices, and cluster routers maybe involved in server device operations.

Data storage 204 may be data storage arrays that include drive arraycontrollers configured to manage read and write access to groups of harddisk drives and/or solid state drives. The drive array controllers,alone or in conjunction with server devices 202, may also be configuredto manage backup or redundant copies of the data stored in data storage204 to protect against drive failures or other types of failures thatprevent one or more of server devices 202 from accessing units of datastorage 204. Other types of memory aside from drives may be used.

Routers 206 may include networking equipment configured to provideinternal and external communications for server cluster 200. Forexample, routers 206 may include one or more packet-switching and/orrouting devices (including switches and/or gateways) configured toprovide (i) network communications between server devices 202 and datastorage 204 via local cluster network 208, and/or (ii) networkcommunications between the server cluster 200 and other devices viacommunication link 210 to network 212.

Additionally, the configuration of routers 206 can be based at least inpart on the data communication requirements of server devices 202 anddata storage 204, the latency and throughput of the local clusternetwork 208, the latency, throughput, and cost of communication link210, and/or other factors that may contribute to the cost, speed,fault-tolerance, resiliency, efficiency and/or other design goals of thesystem architecture.

As a possible example, data storage 204 may include any form ofdatabase, such as a structured query language (SQL) database. Varioustypes of data structures may store the information in such a database,including but not limited to tables, arrays, lists, trees, and tuples.Furthermore, any databases in data storage 204 may be monolithic ordistributed across multiple physical devices.

Server devices 202 may be configured to transmit data to and receivedata from data storage 204. This transmission and retrieval may take theform of SQL queries or other types of database queries, and the outputof such queries, respectively. Additional text, images, video, and/oraudio may be included as well. Furthermore, server devices 202 mayorganize the received data into web page representations. Such arepresentation may take the form of a markup language, such as thehypertext markup language (HTML), the extensible markup language (XML),or some other standardized or proprietary format. Moreover, serverdevices 202 may have the capability of executing various types ofcomputerized scripting languages, such as but not limited to Perl,Python, PHP Hypertext Preprocessor (PHP), Active Server Pages (ASP),JAVASCRIPT®, and so on. Computer program code written in these languagesmay facilitate the providing of web pages to client devices, as well asclient device interaction with the web pages.

III. EXAMPLE REMOTE NETWORK MANAGEMENT ARCHITECTURE

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments. This architecture includes three maincomponents, managed network 300, remote network management platform 320,and third-party networks 340, all connected by way of Internet 350.

Managed network 300 may be, for example, an enterprise network used byan entity for computing and communications tasks, as well as storage ofdata. Thus, managed network 300 may include various client devices 302,server devices 304, routers 306, virtual machines 308, firewall 310,and/or proxy servers 312. Client devices 302 may be embodied bycomputing device 100, server devices 304 may be embodied by computingdevice 100 or server cluster 200, and routers 306 may be any type ofrouter, switch, or gateway.

Virtual machines 308 may be embodied by one or more of computing device100 or server cluster 200. In general, a virtual machine is an emulationof a computing system, and mimics the functionality (e.g., processor,memory, and communication resources) of a physical computer. Onephysical computing system, such as server cluster 200, may support up tothousands of individual virtual machines. In some embodiments, virtualmachines 308 may be managed by a centralized server device orapplication that facilitates allocation of physical computing resourcesto individual virtual machines, as well as performance and errorreporting. Enterprises often employ virtual machines in order toallocate computing resources in an efficient, as needed fashion.Providers of virtualized computing systems include VMWARE® andMICROSOFT®.

Firewall 310 may be one or more specialized routers or server devicesthat protect managed network 300 from unauthorized attempts to accessthe devices, applications, and services therein, while allowingauthorized communication that is initiated from managed network 300.Firewall 310 may also provide intrusion detection, web filtering, virusscanning, application-layer gateways, and other applications orservices. In some embodiments not shown in FIG. 3, managed network 300may include one or more virtual private network (VPN) gateways withwhich it communicates with remote network management platform 320 (seebelow).

Managed network 300 may also include one or more proxy servers 312. Anembodiment of proxy servers 312 may be a server device that facilitatescommunication and movement of data between managed network 300, remotenetwork management platform 320, and third-party networks 340. Inparticular, proxy servers 312 may be able to establish and maintainsecure communication sessions with one or more computational instancesof remote network management platform 320. By way of such a session,remote network management platform 320 may be able to discover andmanage aspects of the architecture and configuration of managed network300 and its components. Possibly with the assistance of proxy servers312, remote network management platform 320 may also be able to discoverand manage aspects of third-party networks 340 that are used by managednetwork 300.

Firewalls, such as firewall 310, typically deny all communicationsessions that are incoming by way of Internet 350, unless such a sessionwas ultimately initiated from behind the firewall (i.e., from a deviceon managed network 300) or the firewall has been explicitly configuredto support the session. By placing proxy servers 312 behind firewall 310(e.g., within managed network 300 and protected by firewall 310), proxyservers 312 may be able to initiate these communication sessions throughfirewall 310. Thus, firewall 310 might not have to be specificallyconfigured to support incoming sessions from remote network managementplatform 320, thereby avoiding potential security risks to managednetwork 300.

In some cases, managed network 300 may consist of a few devices and asmall number of networks. In other deployments, managed network 300 mayspan multiple physical locations and include hundreds of networks andhundreds of thousands of devices. Thus, the architecture depicted inFIG. 3 is capable of scaling up or down by orders of magnitude.

Furthermore, depending on the size, architecture, and connectivity ofmanaged network 300, a varying number of proxy servers 312 may bedeployed therein. For example, each one of proxy servers 312 may beresponsible for communicating with remote network management platform320 regarding a portion of managed network 300. Alternatively oradditionally, sets of two or more proxy servers may be assigned to sucha portion of managed network 300 for purposes of load balancing,redundancy, and/or high availability.

Remote network management platform 320 is a hosted environment thatprovides aPaaS services to users, particularly to the operators ofmanaged network 300. These services may take the form of web-basedportals, for instance. Thus, a user can securely access remote networkmanagement platform 320 from, for instance, client devices 302, orpotentially from a client device outside of managed network 300. By wayof the web-based portals, users may design, test, and deployapplications, generate reports, view analytics, and perform other tasks.

As shown in FIG. 3, remote network management platform 320 includes fourcomputational instances 322, 324, 326, and 328. Each of these instancesmay represent one or more server devices and/or one or more databasesthat provide a set of web portals, services, and applications (e.g., awholly-functioning aPaaS system) available to a particular customer. Insome cases, a single customer may use multiple computational instances.For example, managed network 300 may be an enterprise customer of remotenetwork management platform 320, and may use computational instances322, 324, and 326. The reason for providing multiple instances to onecustomer is that the customer may wish to independently develop, test,and deploy its applications and services. Thus, computational instance322 may be dedicated to application development related to managednetwork 300, computational instance 324 may be dedicated to testingthese applications, and computational instance 326 may be dedicated tothe live operation of tested applications and services. A computationalinstance may also be referred to as a hosted instance, a remoteinstance, a customer instance, or by some other designation. Anyapplication deployed onto a computational instance may be a scopedapplication, in that its access to databases within the computationalinstance can be restricted to certain elements therein (e.g., one ormore particular database tables or particular rows with one or moredatabase tables).

For purpose of clarity, the disclosure herein refers to the physicalhardware, software, and arrangement thereof as a “computationalinstance.” Note that users may colloquially refer to the graphical userinterfaces provided thereby as “instances.” But unless it is definedotherwise herein, a “computational instance” is a computing systemdisposed within remote network management platform 320.

The multi-instance architecture of remote network management platform320 is in contrast to conventional multi-tenant architectures, overwhich multi-instance architectures have several advantages. Inmulti-tenant architectures, data from different customers (e.g.,enterprises) are comingled in a single database. While these customers'data are separate from one another, the separation is enforced by thesoftware that operates the single database. As a consequence, a securitybreach in this system may impact all customers' data, creatingadditional risk, especially for entities subject to governmental,healthcare, and/or financial regulation. Furthermore, any databaseoperations that impact one customer will likely impact all customerssharing that database. Thus, if there is an outage due to hardware orsoftware errors, this outage affects all such customers. Likewise, ifthe database is to be upgraded to meet the needs of one customer, itwill be unavailable to all customers during the upgrade process. Often,such maintenance windows will be long, due to the size of the shareddatabase.

In contrast, the multi-instance architecture provides each customer withits own database in a dedicated computing instance. This preventscomingling of customer data, and allows each instance to beindependently managed. For example, when one customer's instanceexperiences an outage due to errors or an upgrade, other computationalinstances are not impacted. Maintenance down time is limited because thedatabase only contains one customer's data. Further, the simpler designof the multi-instance architecture allows redundant copies of eachcustomer database and instance to be deployed in a geographicallydiverse fashion. This facilitates high availability, where the liveversion of the customer's instance can be moved when faults are detectedor maintenance is being performed.

In some embodiments, remote network management platform 320 may includeone or more central instances, controlled by the entity that operatesthis platform. Like a computational instance, a central instance mayinclude some number of physical or virtual servers and database devices.Such a central instance may serve as a repository for data that can beshared amongst at least some of the computational instances. Forinstance, definitions of common security threats that could occur on thecomputational instances, software packages that are commonly discoveredon the computational instances, and/or an application store forapplications that can be deployed to the computational instances mayreside in a central instance. Computational instances may communicatewith central instances by way of well-defined interfaces in order toobtain this data.

In order to support multiple computational instances in an efficientfashion, remote network management platform 320 may implement aplurality of these instances on a single hardware platform. For example,when the aPaaS system is implemented on a server cluster such as servercluster 200, it may operate a virtual machine that dedicates varyingamounts of computational, storage, and communication resources toinstances. But full virtualization of server cluster 200 might not benecessary, and other mechanisms may be used to separate instances. Insome examples, each instance may have a dedicated account and one ormore dedicated databases on server cluster 200. Alternatively,computational instance 322 may span multiple physical devices.

In some cases, a single server cluster of remote network managementplatform 320 may support multiple independent enterprises. Furthermore,as described below, remote network management platform 320 may includemultiple server clusters deployed in geographically diverse data centersin order to facilitate load balancing, redundancy, and/or highavailability.

Third-party networks 340 may be remote server devices (e.g., a pluralityof server clusters such as server cluster 200) that can be used foroutsourced computational, data storage, communication, and servicehosting operations. These servers may be virtualized (i.e., the serversmay be virtual machines). Examples of third-party networks 340 mayinclude AMAZON WEB SERVICES® and MICROSOFT® AZURE®. Like remote networkmanagement platform 320, multiple server clusters supporting third-partynetworks 340 may be deployed at geographically diverse locations forpurposes of load balancing, redundancy, and/or high availability.

Managed network 300 may use one or more of third-party networks 340 todeploy applications and services to its clients and customers. Forinstance, if managed network 300 provides online music streamingservices, third-party networks 340 may store the music files and provideweb interface and streaming capabilities. In this way, the enterprise ofmanaged network 300 does not have to build and maintain its own serversfor these operations.

Remote network management platform 320 may include modules thatintegrate with third-party networks 340 to expose virtual machines andmanaged services therein to managed network 300. The modules may allowusers to request virtual resources and provide flexible reporting forthird-party networks 340. In order to establish this functionality, auser from managed network 300 might first establish an account withthird-party networks 340, and request a set of associated resources.Then, the user may enter the account information into the appropriatemodules of remote network management platform 320. These modules maythen automatically discover the manageable resources in the account, andalso provide reports related to usage, performance, and billing.

Internet 350 may represent a portion of the global Internet. However,Internet 350 may alternatively represent a different type of network,such as a private wide-area or local-area packet-switched network.

FIG. 4 further illustrates the communication environment between managednetwork 300 and computational instance 322, and introduces additionalfeatures and alternative embodiments. In FIG. 4, computational instance322 is replicated across data centers 400A and 400B. These data centersmay be geographically distant from one another, perhaps in differentcities or different countries. Each data center includes supportequipment that facilitates communication with managed network 300, aswell as remote users.

In data center 400A, network traffic to and from external devices flowseither through VPN gateway 402A or firewall 404A. VPN gateway 402A maybe peered with VPN gateway 412 of managed network 300 by way of asecurity protocol such as Internet Protocol Security (IPSEC) orTransport Layer Security (TLS). Firewall 404A may be configured to allowaccess from authorized users, such as user 414 and remote user 416, andto deny access to unauthorized users. By way of firewall 404A, theseusers may access computational instance 322, and possibly othercomputational instances. Load balancer 406A may be used to distributetraffic amongst one or more physical or virtual server devices that hostcomputational instance 322. Load balancer 406A may simplify user accessby hiding the internal configuration of data center 400A, (e.g.,computational instance 322) from client devices. For instance, ifcomputational instance 322 includes multiple physical or virtualcomputing devices that share access to multiple databases, load balancer406A may distribute network traffic and processing tasks across thesecomputing devices and databases so that no one computing device ordatabase is significantly busier than the others. In some embodiments,computational instance 322 may include VPN gateway 402A, firewall 404A,and load balancer 406A.

Data center 400B may include its own versions of the components in datacenter 400A. Thus, VPN gateway 402B, firewall 404B, and load balancer406B may perform the same or similar operations as VPN gateway 402A,firewall 404A, and load balancer 406A, respectively. Further, by way ofreal-time or near-real-time database replication and/or otheroperations, computational instance 322 may exist simultaneously in datacenters 400A and 400B.

Data centers 400A and 400B as shown in FIG. 4 may facilitate redundancyand high availability. In the configuration of FIG. 4, data center 400Ais active and data center 400B is passive. Thus, data center 400A isserving all traffic to and from managed network 300, while the versionof computational instance 322 in data center 400B is being updated innear-real-time. Other configurations, such as one in which both datacenters are active, may be supported.

Should data center 400A fail in some fashion or otherwise becomeunavailable to users, data center 400B can take over as the active datacenter. For example, domain name system (DNS) servers that associate adomain name of computational instance 322 with one or more InternetProtocol (IP) addresses of data center 400A may re-associate the domainname with one or more IP addresses of data center 400B. After thisre-association completes (which may take less than one second or severalseconds), users may access computational instance 322 by way of datacenter 400B.

FIG. 4 also illustrates a possible configuration of managed network 300.As noted above, proxy servers 312 and user 414 may access computationalinstance 322 through firewall 310. Proxy servers 312 may also accessconfiguration items 410. In FIG. 4, configuration items 410 may refer toany or all of client devices 302, server devices 304, routers 306, andvirtual machines 308, any applications or services executing thereon, aswell as relationships between devices, applications, and services. Thus,the term “configuration items” may be shorthand for any physical orvirtual device, or any application or service remotely discoverable ormanaged by computational instance 322, or relationships betweendiscovered devices, applications, and services. Configuration items maybe represented in a configuration management database (CMDB) ofcomputational instance 322.

As noted above, VPN gateway 412 may provide a dedicated VPN to VPNgateway 402A. Such a VPN may be helpful when there is a significantamount of traffic between managed network 300 and computational instance322, or security policies otherwise suggest or require use of a VPNbetween these sites. In some embodiments, any device in managed network300 and/or computational instance 322 that directly communicates via theVPN is assigned a public IP address. Other devices in managed network300 and/or computational instance 322 may be assigned private IPaddresses (e.g., IP addresses selected from the 10.0.0.0-10.255.255.255or 192.168.0.0-192.168.255.255 ranges, represented in shorthand assubnets 10.0.0.0/8 and 192.168.0.0/16, respectively).

IV. EXAMPLE DEVICE, APPLICATION, AND SERVICE DISCOVERY

In order for remote network management platform 320 to administer thedevices, applications, and services of managed network 300, remotenetwork management platform 320 may first determine what devices arepresent in managed network 300, the configurations and operationalstatuses of these devices, and the applications and services provided bythe devices, and well as the relationships between discovered devices,applications, and services. As noted above, each device, application,service, and relationship may be referred to as a configuration item.The process of defining configuration items within managed network 300is referred to as discovery, and may be facilitated at least in part byproxy servers 312.

For purpose of the embodiments herein, an “application” may refer to oneor more processes, threads, programs, client modules, server modules, orany other software that executes on a device or group of devices. A“service” may refer to a high-level capability provided by multipleapplications executing on one or more devices working in conjunctionwith one another. For example, a high-level web service may involvemultiple web application server threads executing on one device andaccessing information from a database application that executes onanother device.

FIG. 5A provides a logical depiction of how configuration items can bediscovered, as well as how information related to discoveredconfiguration items can be stored. For sake of simplicity, remotenetwork management platform 320, third-party networks 340, and Internet350 are not shown.

In FIG. 5A, CMDB 500 and task list 502 are stored within computationalinstance 322. Computational instance 322 may transmit discovery commandsto proxy servers 312. In response, proxy servers 312 may transmit probesto various devices, applications, and services in managed network 300.These devices, applications, and services may transmit responses toproxy servers 312, and proxy servers 312 may then provide informationregarding discovered configuration items to CMDB 500 for storagetherein. Configuration items stored in CMDB 500 represent theenvironment of managed network 300.

Task list 502 represents a list of activities that proxy servers 312 areto perform on behalf of computational instance 322. As discovery takesplace, task list 502 is populated. Proxy servers 312 repeatedly querytask list 502, obtain the next task therein, and perform this task untiltask list 502 is empty or another stopping condition has been reached.

To facilitate discovery, proxy servers 312 may be configured withinformation regarding one or more subnets in managed network 300 thatare reachable by way of proxy servers 312. For instance, proxy servers312 may be given the IP address range 192.168.0/24 as a subnet. Then,computational instance 322 may store this information in CMDB 500 andplace tasks in task list 502 for discovery of devices at each of theseaddresses.

FIG. 5A also depicts devices, applications, and services in managednetwork 300 as configuration items 504, 506, 508, 510, and 512. As notedabove, these configuration items represent a set of physical and/orvirtual devices (e.g., client devices, server devices, routers, orvirtual machines), applications executing thereon (e.g., web servers,email servers, databases, or storage arrays), relationshipstherebetween, as well as services that involve multiple individualconfiguration items.

Placing the tasks in task list 502 may trigger or otherwise cause proxyservers 312 to begin discovery. Alternatively or additionally, discoverymay be manually triggered or automatically triggered based on triggeringevents (e.g., discovery may automatically begin once per day at aparticular time).

In general, discovery may proceed in four logical phases: scanning,classification, identification, and exploration. Each phase of discoveryinvolves various types of probe messages being transmitted by proxyservers 312 to one or more devices in managed network 300. The responsesto these probes may be received and processed by proxy servers 312, andrepresentations thereof may be transmitted to CMDB 500. Thus, each phasecan result in more configuration items being discovered and stored inCMDB 500.

In the scanning phase, proxy servers 312 may probe each IP address inthe specified range of IP addresses for open Transmission ControlProtocol (TCP) and/or User Datagram Protocol (UDP) ports to determinethe general type of device. The presence of such open ports at an IPaddress may indicate that a particular application is operating on thedevice that is assigned the IP address, which in turn may identify theoperating system used by the device. For example, if TCP port 135 isopen, then the device is likely executing a WINDOWS® operating system.Similarly, if TCP port 22 is open, then the device is likely executing aUNIX® operating system, such as LINUX®. If UDP port 161 is open, thenthe device may be able to be further identified through the SimpleNetwork Management Protocol (SNMP). Other possibilities exist. Once thepresence of a device at a particular IP address and its open ports havebeen discovered, these configuration items are saved in CMDB 500.

In the classification phase, proxy servers 312 may further probe eachdiscovered device to determine the version of its operating system. Theprobes used for a particular device are based on information gatheredabout the devices during the scanning phase. For example, if a device isfound with TCP port 22 open, a set of UNIX®-specific probes may be used.Likewise, if a device is found with TCP port 135 open, a set ofWINDOWS®-specific probes may be used. For either case, an appropriateset of tasks may be placed in task list 502 for proxy servers 312 tocarry out. These tasks may result in proxy servers 312 logging on, orotherwise accessing information from the particular device. Forinstance, if TCP port 22 is open, proxy servers 312 may be instructed toinitiate a Secure Shell (SSH) connection to the particular device andobtain information about the operating system thereon from particularlocations in the file system. Based on this information, the operatingsystem may be determined. As an example, a UNIX® device with TCP port 22open may be classified as AIX®, HPUX, LINUX®, MACOS®, or SOLARIS®. Thisclassification information may be stored as one or more configurationitems in CMDB 500.

In the identification phase, proxy servers 312 may determine specificdetails about a classified device. The probes used during this phase maybe based on information gathered about the particular devices during theclassification phase. For example, if a device was classified as LINUX®,a set of LINUX®-specific probes may be used. Likewise, if a device wasclassified as WINDOWS® 2012, as a set of WINDOWS®-2012-specific probesmay be used. As was the case for the classification phase, anappropriate set of tasks may be placed in task list 502 for proxyservers 312 to carry out. These tasks may result in proxy servers 312reading information from the particular device, such as basicinput/output system (BIOS) information, serial numbers, networkinterface information, media access control address(es) assigned tothese network interface(s), IP address(es) used by the particular deviceand so on. This identification information may be stored as one or moreconfiguration items in CMDB 500.

In the exploration phase, proxy servers 312 may determine furtherdetails about the operational state of a classified device. The probesused during this phase may be based on information gathered about theparticular devices during the classification phase and/or theidentification phase. Again, an appropriate set of tasks may be placedin task list 502 for proxy servers 312 to carry out. These tasks mayresult in proxy servers 312 reading additional information from theparticular device, such as processor information, memory information,lists of running processes (applications), and so on. Once more, thediscovered information may be stored as one or more configuration itemsin CMDB 500.

Running discovery on a network device, such as a router, may utilizeSNMP. Instead of or in addition to determining a list of runningprocesses or other application-related information, discovery maydetermine additional subnets known to the router and the operationalstate of the router's network interfaces (e.g., active, inactive, queuelength, number of packets dropped, etc.). The IP addresses of theadditional subnets may be candidates for further discovery procedures.Thus, discovery may progress iteratively or recursively.

Once discovery completes, a snapshot representation of each discovereddevice, application, and service is available in CMDB 500. For example,after discovery, operating system version, hardware configuration andnetwork configuration details for client devices, server devices, androuters in managed network 300, as well as applications executingthereon, may be stored. This collected information may be presented to auser in various ways to allow the user to view the hardware compositionand operational status of devices, as well as the characteristics ofservices that span multiple devices and applications.

Furthermore, CMDB 500 may include entries regarding dependencies andrelationships between configuration items. More specifically, anapplication that is executing on a particular server device, as well asthe services that rely on this application, may be represented as suchin CMDB 500. For instance, suppose that a database application isexecuting on a server device, and that this database application is usedby a new employee onboarding service as well as a payroll service. Thus,if the server device is taken out of operation for maintenance, it isclear that the employee onboarding service and payroll service will beimpacted. Likewise, the dependencies and relationships betweenconfiguration items may be able to represent the services impacted whena particular router fails.

In general, dependencies and relationships between configuration itemsmay be displayed on a web-based interface and represented in ahierarchical fashion. Thus, adding, changing, or removing suchdependencies and relationships may be accomplished by way of thisinterface.

Furthermore, users from managed network 300 may develop workflows thatallow certain coordinated activities to take place across multiplediscovered devices. For instance, an IT workflow might allow the user tochange the common administrator password to all discovered LINUX®devices in a single operation.

In order for discovery to take place in the manner described above,proxy servers 312, CMDB 500, and/or one or more credential stores may beconfigured with credentials for one or more of the devices to bediscovered. Credentials may include any type of information needed inorder to access the devices. These may include userid/password pairs,certificates, and so on. In some embodiments, these credentials may bestored in encrypted fields of CMDB 500. Proxy servers 312 may containthe decryption key for the credentials so that proxy servers 312 can usethese credentials to log on to or otherwise access devices beingdiscovered.

The discovery process is depicted as a flow chart in FIG. 5B. At block520, the task list in the computational instance is populated, forinstance, with a range of IP addresses. At block 522, the scanning phasetakes place. Thus, the proxy servers probe the IP addresses for devicesusing these IP addresses, and attempt to determine the operating systemsthat are executing on these devices. At block 524, the classificationphase takes place. The proxy servers attempt to determine the operatingsystem version of the discovered devices. At block 526, theidentification phase takes place. The proxy servers attempt to determinethe hardware and/or software configuration of the discovered devices. Atblock 528, the exploration phase takes place. The proxy servers attemptto determine the operational state and applications executing on thediscovered devices. At block 530, further editing of the configurationitems representing the discovered devices and applications may takeplace. This editing may be automated and/or manual in nature.

The blocks represented in FIG. 5B are for purpose of example. Discoverymay be a highly configurable procedure that can have more or fewerphases, and the operations of each phase may vary. In some cases, one ormore phases may be customized, or may otherwise deviate from theexemplary descriptions above.

V. CMDB IDENTIFICATION RULES AND RECONCILIATION

A CMDB, such as CMDB 500, provides a repository of configuration items,and when properly provisioned, can take on a key role in higher-layerapplications deployed within or involving a computational instance.These applications may relate to enterprise IT service management,operations management, asset management, configuration management,compliance, and so on.

For example, an IT service management application may use information inthe CMDB to determine applications and services that may be impacted bya component (e.g., a server device) that has malfunctioned, crashed, oris heavily loaded. Likewise, an asset management application may useinformation in the CMDB to determine which hardware and/or softwarecomponents are being used to support particular enterprise applications.As a consequence of the importance of the CMDB, it is desirable for theinformation stored therein to be accurate, consistent, and up to date.

A CMDB may be populated in various ways. As discussed above, a discoveryprocedure may automatically store information related to configurationitems in the CMDB. However, a CMDB can also be populated, as a whole orin part, by manual entry, configuration files, and third-party datasources. Given that multiple data sources may be able to update the CMDBat any time, it is possible that one data source may overwrite entriesof another data source. Also, two data sources may each create slightlydifferent entries for the same configuration item, resulting in a CMDBcontaining duplicate data. When either of these occurrences takes place,they can cause the health and utility of the CMDB to be reduced.

In order to mitigate this situation, these data sources might not writeconfiguration items directly to the CMDB. Instead, they may write to anidentification and reconciliation application programming interface(API). This API may use a set of configurable identification rules thatcan be used to uniquely identify configuration items and determinewhether and how they are written to the CMDB.

In general, an identification rule specifies a set of configuration itemattributes that can be used for this unique identification.Identification rules may also have priorities so that rules with higherpriorities are considered before rules with lower priorities.Additionally, a rule may be independent, in that the rule identifiesconfiguration items independently of other configuration items.Alternatively, the rule may be dependent, in that the rule first uses ametadata rule to identify a dependent configuration item.

Metadata rules describe which other configuration items are containedwithin a particular configuration item, or the host on which aparticular configuration item is deployed. For example, a networkdirectory service configuration item may contain a domain controllerconfiguration item, while a web server application configuration itemmay be hosted on a server device configuration item.

A goal of each identification rule is to use a combination of attributesthat can unambiguously distinguish a configuration item from all otherconfiguration items, and is expected not to change during the lifetimeof the configuration item. Some possible attributes for an exampleserver device may include serial number, location, operating system,operating system version, memory capacity, and so on. If a rulespecifies attributes that do not uniquely identify the configurationitem, then multiple components may be represented as the sameconfiguration item in the CMDB. Also, if a rule specifies attributesthat change for a particular configuration item, duplicate configurationitems may be created.

Thus, when a data source provides information regarding a configurationitem to the identification and reconciliation API, the API may attemptto match the information with one or more rules. If a match is found,the configuration item is written to the CMDB. If a match is not found,the configuration item may be held for further analysis.

Configuration item reconciliation procedures may be used to ensure thatonly authoritative data sources are allowed to overwrite configurationitem data in the CMDB. This reconciliation may also be rules-based. Forinstance, a reconciliation rule may specify that a particular datasource is authoritative for a particular configuration item type and setof attributes. Then, the identification and reconciliation API will onlypermit this authoritative data source to write to the particularconfiguration item, and writes from unauthorized data sources may beprevented. Thus, the authorized data source becomes the single source oftruth regarding the particular configuration item. In some cases, anunauthorized data source may be allowed to write to a configuration itemif it is creating the configuration item or the attributes to which itis writing are empty.

Additionally, multiple data sources may be authoritative for the sameconfiguration item or attributes thereof. To avoid ambiguities, thesedata sources may be assigned precedences that are taken into accountduring the writing of configuration items. For example, a secondaryauthorized data source may be able to write to a configuration item'sattribute until a primary authorized data source writes to thisattribute. Afterward, further writes to the attribute by the secondaryauthorized data source may be prevented.

In some cases, duplicate configuration items may be automaticallydetected by reconciliation procedures or in another fashion. Theseconfiguration items may be flagged for manual de-duplication.

VI. EXAMPLE REMOTE COMPUTING SYSTEM ARCHITECTURE

FIG. 6 illustrates an example architecture of a remote computing system.The remote computing system may provide a cloud-based computingenvironment that allows managed network 300 to host softwareapplications, store data, and otherwise utilize remotely-hostedcomputing resources. The cloud-based computing environment may beprovided atop an infrastructure of various computing resources thatallow the computing environment to be defined, modified, and otherwisetailored to the needs of managed network 300. The remote computingsystem may be GOOGLE CLOUD PLATFORM®, IBM CLOUD®, MICROSOFT® AZURE®,and/or AMAZON WEB SERVICES®, among other possible cloud providers.

The cloud-based computing environment may be configured to automaticallyscale as demand for the computing resources vary over time. Accordingly,the state of the infrastructure of computing resources may alsofluctuate over time to allow for such scaling. The extent of scaling andfluctuation in the computing resources dedicated to managed network 300may indicate a popularity (e.g., absolute popularity and/or relativepopularity) of the services provided by managed network 300. This mayresult in variable costs of using the cloud-based computing environment.Thus, maintaining an accurate and up-to-date map of the serviceinfrastructure dedicated by the remote computing system to managednetwork 300 may allow managed network 300 to more effectively and/orefficiently utilize the cloud-based computing environment. To that end,managed network 300 may utilize a discovery application to discover andmap the service infrastructure, and subsequently modify aspects thereofto reach a target state.

The computing infrastructure provided by the remote computing system maybe organized into multiple different geographic regions. Each geographicregion may encompass a geographic area in which multiple different andphysically separate data centers are located. For example, the regionsmay include United States South (i.e., US-South), US-East, EuropeanUnion Great Britain (i.e., EU-GB), EU-Germany, and Asia Pacific North(i.e., AP-North), among other possibilities. Different remote computingsystems may implement a different set of regions. Allocating computingresources within a particular geographic region allows client deviceswithin or nearby this region to more quickly communicate with thecomputing resources therein.

Region 600 is an example region of the remote computing system. Althoughnot shown, the remote computing system may include multiplegeographically-distributed instantiations of region 600 and one or moreof its components. Managed network 300 may be assigned a plurality ofcomputing resources within region 600 that make up at least part of thecloud-based computing environment. Namely, region 600 includesavailability zone 604 and availability zone 606, each of which mayrepresent a corresponding physical data center. In some implementations,the underlying hardware that makes up each of availability zones 604 and606 may be physically isolated, such that outages (e.g., power outages)associated with one availability zone do not affect the otheravailability zone. Accordingly, availability zones may provideredundancy within a single geographic region.

Each of availability zones 604 and 606 may be part of network 602dedicated to managed network 300 by the remote computing system. Network602 may allow client devices (e.g., computing devices external to theremote computing system) access to computing resources in availabilityzones 604 and/or 606 and may also allow these computing resources tocommunicate with one another. In some embodiments, network 602 may bereferred to as a Virtual Private Cloud (VPC). Each availability zonesmay be assigned a corresponding subnet, thus allowing for a logicaldivision (e.g., based on IP address) of the computing resources providedby each availability zone. That is, availability zone 604 may beassigned subnet 608 while availability zone 606 may be assigned subnet610.

Network 602 also includes Internet gateway 612, route table and networkaccess control list (NACL) 614 for subnet 608, and route table and NACL616 for subnet 610. Internet gateway 612 may provide an interfacebetween components of network 602 and the Internet (e.g., computingdevices outside of network 602). Route tables and NACLs 614 and 616 mayprovide network traffic control to subnets 608 and 610, respectively.Among other network parameters, route table and NACL 614 may definepermitted destinations for and permitted types of traffic originatingout of computing resources in subnet 608, as well as permitted sourcesand permitted types of traffic addressed to computing resources insubnet 608. For example, route table and NACL 614 may indicate whethersubnet 608 is accessible to computing devices outside of network 602(i.e., whether subnet 608 is public or private). Route table and NACL616 may define similar rules for subnet 610.

Internet gateway 612, as well as route tables and NACLs 614 and 616, mayrepresent logical components of the remote computing system. That isInternet gateway 612, route table and NACL 614, and/or route table andNACL 616 may be implemented by one or more physical devices (e.g.,gateways and routers) of the remote computing system. Additionally, insome implementations of a remote computing system, network 602 mayextend across, cover, or include multiple different instantiations ofregion 600.

Each availability zone may include therein a corresponding plurality ofcomputing resources. Namely, availability zone 604 (and subnet 608) mayinclude therein load balancer 620, virtual computing devices 622 and 624through 626 (i.e., virtual computing devices 622-626), and storagevolumes 628 and 630. Similarly, availability zone 606 (and subnet 610)may include therein load balancer 640, virtual computing devices 642 and644 through 646 (i.e., virtual computing devices 642-646), and storagevolumes 648 and 650. A virtual computing device may alternatively bereferred to as a virtual machine.

In some implementations, each of load balancers 620 and 640, virtualcomputing devices 622-626 and 642-646, and storage volumes 628, 630,648, and 650 may represent physical computing resources of the remotecomputing system. For example, virtual computing device 622 mayrepresent a physical computing device used exclusively for computation,but not other tasks such as providing storage or load balancing.Alternatively, each of these computing resources may represent virtualcomputing resources (e.g., software processes that isolate theimplementation of the computing resource from the underlying physicalhardware). Thus, for example, each physical computing device within theremote computing system may execute and provide multiple virtualcomputing resources, including computation, load balancing, and storage.

Load balancer 640 may be configured to distribute network traffic (e.g.,web traffic generated by various software applications) or other typesof requests among virtual computing devices 642-646. Thus, load balancer640 may balance traffic within a single availability zone. On the otherhand, load balancer 620 may be configured to distribute network trafficamong virtual computing devices 622-626 and 642. Thus, load balancer 620may be configured to balance traffic across multiple availability zones.When load balancers 620 and/or 640 are accessible by computing devicesoutside of network 602 (or one or more other networks in othergeographic regions of the remote computing system), they may beconsidered public load balancers. On the other hand, when load balancers620 and/or 640 are accessible only by computing resources within network602, they may be considered private load balancers.

Virtual computing devices 622-626 and 642-646 may each be configurableto provide a target amount of computing resources. For example, thenumber of processor cores dedicated to execution of each virtualcomputing device, the amount of memory available to each virtualcomputing device, and the operating system executed by each virtualcomputing device may be adjustable for each of virtual computing devices622-626 and 642-646. Virtual computing devices 622-626 and 642-646 mayutilize storage volumes 628, 630, 648, and 650 to store various dataassociated with the software executed by these virtual computingdevices. Specifically, virtual computing device 622 may utilize storagevolume 628, virtual computing device 624 and 626 may utilize storagevolume 630, virtual computing devices 642 may utilize storage volume648, and virtual computing devices 644 and 646 may utilize storagevolume 650.

These and other aspects of the remote computing system may bediscoverable, mappable, and modifiable by the discovery application.Specifically, the discovery application may utilize an API, a commandline interface, or another mechanism provided by the remote computingsystem to determine and adjust the service infrastructure dedicated tomanaged network 300 by the remote computing system. Specifically, thediscovery application may obtain attributes of the various computingresources provided by the remote computing system and, based on theattributes, determine how these different computing resources coordinatewith one another. The computing resources, their attributes, and therelationships therebetween may be represented as a map to allow for avisualization of the service infrastructure. The map may, in turn, beused to identify modifications and adjustments to a current state of theinfrastructure that allow a target infrastructure state to be reached.

VII. EXAMPLE CMDB MODEL OF A REMOTE COMPUTING SYSTEM

FIG. 7 illustrates an example model according to which a mapping ofcomputing resources of a remote computing system may be determined andstored in a CMDB. The discovery application may utilize this model todiscover, map, and modify the computing resources of the remotecomputing system. In some cases, different remote computing systemproviders may use different names to refer to certain computingresources within this model. The discovery application may be configuredto identify a correspondence between portions of the model in FIG. 7 andthe computing resource names used by a particular provider, thusallowing many different remote computing systems to be mapped accordingto this model. Additionally or alternatively, when some remote computingsystems deviate from the model in other ways, the discovery applicationmay be configured to account for such variations by modifying this modelto accurately reflect the infrastructure of these remote computingsystems.

The model of FIG. 7 illustrates the different types of computingresources found in a remote computing system, as well as how thesedifferent computing resources relate to one another. Notably, the modelincludes one box per type of computing resource. However, a map of thecomputing resources determined based on the model may include multipleinstantiations of each of the boxes making up the model. Thus, the mapmay reflect an actual state of the infrastructure and may be determinedbased on resource types and the relationships therebetween illustratedin the model.

Discovery may be initiated by specifying, by way of the discoveryapplication, service account 704 and credentials 706 therefor. Asindicated by the model key in the upper right corner of FIG. 7,credentials 706 are used by service account 704. Service account 704 andcredentials 706 may collectively be referred to as a service identifiersince they allow the discovery application to access, on behalf ofmanaged network 300, the specific portions of the remote computingsystem that are dedicated to managed network 300, thus enabling thediscovery process. Credentials 706 may take the form of a username andpassword or a web token (e.g., a JavaScript Object Notation (JSON) WebToken), among other possibilities.

Service account 704 may identify region 710 in which computing resourcesare dedicated to managed network 300 by the remote computing system. Asindicated by the model key, region 710 may be considered to be hosted onservice account 704. Similarly, network 702 and availability zone 708are hosted on region 710. Notably, this relationship is also illustratedin FIG. 6 in that region 600 contains therein network 602 andavailability zones 604 and 606. In some implementations, availabilityzone 708 may also be contained by network 702 (e.g., as shown in FIG.6), although this relationship is not shown in FIG. 7.

Network 702 may define a state of the network (e.g., active vs.inactive), a Classless Inter-Domain Routing (CIDR) block of addressesused by network 702, a virtual local area network (VLAN) number, anddevices that make up the network, among other possible attributes. Bothnetwork 702 and availability zone 708 contain subnet 700. Subnet 700 maydefine a unique name of the subnet, a subnet mask, a CIDR block ofaddresses assigned to the subnet, a number of IP addresses available onthe subnet, and a gateway used by the subnet, among other attributesthereof.

Since network 702 and availability zone 708 are hosted on region 710 andregion 710 is, in turn, hosted on service account 704, network 702 andavailability zone 708 may also be considered to be hosted on serviceaccount 704. Thus, in general, for “hosted on” and “contained by”relationships, a child node (i.e., a box having an “H” or “C” arrowextending therefrom) may also inherit the relationships held by itsparent node (i.e., a box having an “H” or “C” arrow extending thereto).Thus, subnet 700 may be hosted on region 710 and service account 704.

Availability zone 708 may host virtual computing device 720, storagevolume 742, and load balancer 728. Virtual computing device 720 may usenetwork interface controller (NIC) 718 to communicate with othercomputing resources in network 702. Virtual computing device 720 mayalso use security group and rules 726, which effectively provide afirewall for virtual computing device 720. In some embodiments, each ofNIC 718 and security group and rules 726 may have a “contained by”relationship with network 702 (not shown).

Virtual computing device 720 may be provisioned from secure shell (SSH)key 712, operating system (OS) image 714, and hardware 716, each ofwhich may also be hosted on service account 704. SSH key 712 may defineone or more SSH keys used by virtual computing device 720 toauthenticate itself to other computing resources, including computingresources in and outside of the remote computing system. OS image 714may define, among other attributes, the type (e.g., WINDOWS®, LINUX®,etc.) and release version (e.g., WINDOWS® 10) of the operating systemexecuted by virtual computing device 720. Hardware 716 may define theattributes of the underlying physical hardware on which virtualcomputing device 720 is executing. For example, hardware 716 may definethe processor provider (e.g., INTEL®, AMD®), processor model, processorspecifications, and available memory, among other attributes thereof.

Load balancer 728 may host thereon load balancer (LB) service 738 thatcontains LB health service 740 and LB pool 736. Each load balancer 728may provide multiple LB services 738 each corresponding to a differentsoftware application. LB pool 736 may define one or more of virtualcomputing devices 720 among which LB service 738 distributes networktraffic. Accordingly, virtual computing device 720 is shown as having a“contained by” relationship with LB pool 736. LB health service 740 mayindicate how an operational status of LB service 738 is monitored,indicating, for example, how frequently LB service 738 is pinged toverify that it is running (e.g., every five seconds), a maximum timeoutperiod of time after a ping within which a response to the ping isexpected, and a maximum number of failed pings before LB service 738 isterminated and replaced, among other attributes.

Storage volume 742 may implement each of internet small computer systeminterface (ISCSI) endpoint 730, network file system (NFS) endpoint 732,and block endpoint 734. That is, storage volume 742 may provide aplurality of different interfaces (e.g., each implementing a differentprotocol) by way of which virtual computing device 720 can access anduse storage volume 742, as indicated by the corresponding arrows andtheir relationships. Storage volume 742 may be provisioned from volumesnapshot 744, which may define snapshot name, a size of the storagevolume represented thereby, and a source storage volume from which thesnapshot was taken, among other attributes.

The remote computing system may additionally allow managed network todivide the computing resources dedicated thereto into organizations(org.) 722 and spaces 724. Organizations 722 may be hosted on serviceaccount 704, and the computing resources that make up an organizationmay be distributed between multiple regions 710. Different organizations722 may allow managed network 300 to, for example, separately maintainthe computing resources dedicated to different departments withinmanaged network 300. Spaces 724, which are hosted by respectiveorganizations 722, may each be contained within a corresponding region710. Spaces 724 may allow managed network 300 to create multipledifferent isolated computing environments within an organization. Forexample, in the course of development of its software applications, aparticular department within managed network 300 may utilize adevelopment environment, a staging environment, and a productionenvironment, each of which may be created by a separate space.

Notably, as suggested above, each respective computing resource ofcomputing resources 700-744 shown in FIG. 7 may be associated with atleast a unique identifier and one or more attributes of the respectivecomputing resource. In some implementations, the specific attributesprovided or exposed by a particular remote computing system for therespective computing resource may vary. For example, for a particularcomputing resource, a first remote computing system may provide a firstset of attributes while a second remote computing system provides asecond different set of attributes. The model may support thisdifference by including, for the particular computing resource, fieldsfor both the first and second sets of attributes. Thus, depending on thespecific remote computing system undergoing discovery, differentportions of the model may be utilized to generate the map of the serviceinfrastructure. Alternatively, in some cases, each remote computingsystem may be associated with a corresponding variation of the model ofFIG. 7 that includes computing resource types and attribute fieldsspecific to those provided by the particular remote computing system.

VIII. EXAMPLE MAPPING AND DISCOVERY OF REMOTE COMPUTING SYSTEM

FIG. 8 illustrates message diagram of operations involved in discoveringand mapping aspects of a remote computing system. Execution of these andother operations may allow discovery application 800 to determine,according to the model shown in FIG. 7 or a variation thereof, a map ofthe computing resources provided by remote computing system 804 tomanaged network 300. A representation of this map may be stored in CMDB802 as one or more configuration items.

Discovery application 800 and CMDB 802 may be hosted by managed network300, by remote network management platform 320, or distributedtherebetween. CMDB 802 may be stored in persistent storage as one ormore data structures (e.g., database tables). Remote computing system804 may provide API server 806 configured to execute a plurality offunctions. These functions may be remotely accessible by discoveryapplication 800, and may be configured to generate data indicative ofcomputing resources allocated to managed network 300. Namely, byinvoking functions provided by API server 806, discovery application 800may obtain the information necessary to determine the map of thesecomputing resources.

Discovery application 800 may be configured to obtain a serviceidentifier for remote computing system 804, as indicated by block 810.This service identifier may correspond to service account 704 and/orcredentials 706. Accordingly, the service identifier may allow discoveryapplication 800 to access, discover, and/or determine the attributes ofcomputing resources dedicated to managed network 300 by remote computingsystem 804. The service identifier may thus, at least in part, definethe scope of discovery carried out by discovery application 800.

Based on or in response to obtaining the service identifier at block810, discovery application 800 may be configured to identify ageographic region for discovery and mapping, as indicated by block 812.The computing resources dedicated to managed network 300 by remotecomputing system 804 may be distributed among multiple differentgeographic regions. In some cases, each region may provide a differentAPI or a different API function for obtaining information on thecomputing resources located within that region. Alternatively oradditionally, the API may necessitate that discovery application 800specify a particular region as an input parameter of the API function.Thus, identifying the geographic regions that are to be discovered andmapped may allow discovery application 800 to utilize the correct APIsand API functions in subsequent operations.

In some implementations, the different geographic regions utilized bymanaged network 300 may be indicated by the service identifier.Alternatively, discovery application 800 may transmit a query (e.g., ahypertext transfer protocol (HTTP) request) to remote computing system804 (e.g., to API server 806) requesting identification of the differentgeographic regions in which computing resources are dedicated to managednetwork 300. In response to this query, remote computing system 804 mayprovide (e.g., as an HTTP response) a list of one or more regions thatcontain computing resources associated with the service identifier, thusallowing discovery application 800 to further define the scope ofsubsequent discovery operations.

Based on or in response to identifying the geographic region at block812, discovery application 800 may be configured to generate a firstrequest for attributes of virtual computing devices located in thegeographic region, as indicated by block 814. As mentioned above, therequest may specify the geographic region as an input parameter of theAPI function, by calling an API function specific to the geographicregion, or by calling an API specific to the geographic region, amongother possibilities.

When the first request is an HTTP request, the input parameters for thefunction may be provided as HTTP parameters, such as URL resource pathparameters that identify specific resources provided by API server 806,URL query parameters that include key and value pairs, HTTP headerparameters, HTTP cookie parameters, and/or HTTP body parameters.Additionally, the geographic region may be specified by way of the URL.For example, calling an API specific to the geographic region mayinvolve transmitting the first request to REGION.REMOTE SYSTEM.COM/APIFUNCTION, thus specifying the region as a subdomain of the “REMOTESYSTEM” domain. Similarly, calling an API function specific to thegeographic region may involve transmitting the first request to REMOTESYSTEM.COM/REGION/API FUNCTION, thus specifying the region as a resourcepath parameter. Further, specifying the region as an input parameter ofthe API function may involve transmitting the first request to REMOTESYSTEM.COM/API FUNCTION&REGION=SPECIFIC REGION, thus indicating theregion by assigning the query parameter value “SPECIFIC REGION” to queryparameter key “REGION.”

The attributes of the virtual computing devices may include a name orother identifier (e.g., IP address) of the virtual computing device,identifiers of any storage volumes used by the virtual computing device,and/or identifiers of any other aspects of the model shown in FIG. 7that have a relationship with the virtual computing device. Thus, theattributes may indicate other computing resources with which the virtualcomputing devices interact and/or which the virtual computing devicesuse in providing the computing environment. As such, the virtualcomputing devices may serve as a central point for discovery from whichother computing resources dedicated to managed network 300 can bediscovered and mapped. That is, since the virtual computing deviceseither use or are provisioned from many other computing resources withinthe model of FIG. 7, the attributes of the virtual computing devicesfacilitate generation of relationships once these other computingresources are discovered by subsequent discovery operations.

Based on or in response to generating the first request at block 814,discovery application 800 may be configured to transmit, to API server806, the first request, as indicated by arrow 816. In some embodiments,the API of API server 806 may be accessible by way of a command lineinterface. Accordingly, transmitting the first request may involvediscovery application 800 logging in to API server 806 and establishingtherewith a remote shell connection. Discovery application 800 may thencause, by way of the remote shell connection, API server 806 to executeone or more operating system shell commands or scripts. In otherembodiments, the API of API server 806 may be a representational statetransfer (REST) API and may thus be accessible by way of HTTP requests.API server 806 may also be configured to provide, and discoveryapplication 800 configured to utilize, other interfaces for accessingthe functions of the API.

Based on or in response to reception of the request at arrow 816, APIserver 806 may be configured to execute a first API function addressedby the first request, as indicated by block 818. Execution of the firstAPI function may generate an output indicating (i) an identifier of eachrespective virtual computing device dedicated to managed network 300 inthe specified geographic region and (ii) for each respective virtualcomputing device, attributes associated with the respective virtualcomputing device. In some implementations of the API, the attributes ofeach respective virtual computing device may be provided explicitly.That is, the output of the first API function may contain the values ofthe attributes.

In other implementations, the attributes may be provided indirectly bydefining additional requests that discovery application 800 can use toobtain the values of these attributes. For example, when the functionsof API server 806 are accessible by way of web queries, each attributemay be specified by a corresponding URL. Discovery application 800 maybe able to obtain the value of a respective attribute by transmitting anHTTP request to the corresponding URL. Each URL may, for example,address a corresponding function provided by API server 806 that isconfigured to identify and provide the attributes of a specific type ofcomputing resource.

Based on or in response to execution of the first API function at block818, API server 806 may be configured to transmit (e.g., as an HTTPresponse), to discovery application 800, the output of the first APIfunction, as indicated by arrow 820.

Based on or in response to reception of the output at arrow 820,discovery application 800 may be configured to identify, based on theattributes in the output, load balancers and storage volumes associatedwith the virtual computing devices, as indicated by block 822.Specifically, discovery application 800 may be configured to identifyload balancers that distribute traffic among the virtual computingdevices and storage volumes used by the virtual computing devices.

Accordingly, discovery application may be configured to generate one ormore additional requests (e.g., HTTP requests) for attributes of theload balancers and the storage volumes, as indicated by block 824. Basedon or in response to generating the additional requests at block 824,discovery application 800 may be configured to transmit the additionalrequests to API server 806, as indicated by arrow 826. Based on or inresponse to reception of the requests at arrow 826, API server 806 maybe configured to execute additional API functions, as indicated by block828. The additional API functions may be configured to identify andprovide the attributes of storage volumes, storage volume endpoints(e.g., endpoints 730, 732, and/or 734), load balancers, load balancerservices, load balancer pools, and/or load balancer health services.

Based on or in response to execution of the additional API functions,API server 806 may be configured to transmit, to discovery application,an output of the API functions, as indicated by arrow 830. Based on orin response to reception of the transmission at arrow 830, discoveryapplication 800 may be configured to generate a mapping between thevirtual computing devices, the load balancers, and the storage volumes,as indicated by block 832.

Discovery application 800 may be configured to identify a relationshipbetween the load balancers and the virtual computing devices based onthe IP addresses assigned to the virtual computing devices, among otheridentifiers thereof. Specifically, discovery application 800 may beconfigured to identify load balancers whose pools (e.g., LB pools 736)include therein the IP address or other identifier of at least one ofthe discovered virtual computing device. Thus, a load balancer may bedetermined to distribute network traffic to a particular virtualcomputing device when the IP address or other identifier thereof isfound in the LB pool of the load balancer. Through the relationshipbetween the LB pool and the virtual machine, discovery application 800may also identify how the LB services and LB health services relate tothe load balancers and the virtual computing devices.

Discovery application 800 may be configured to identify the storagevolumes used by the virtual computing devices based directly on theattributes of the virtual computing devices. That is, the attributes ofthe virtual computing devices may identify a name, IP address, or otheridentifier of the storage volumes or storage volume endpoints used bythe virtual computing devices. Notably, by causing API server 806 toexecute the additional API functions at block 828, discovery application800 may obtain additional information regarding the storage volumes fromAPI server 806.

Accordingly, discovery application 800 may be configured to parse theoutput generated by the additional API functions for attributes thatindicate relationships with other computing devices. Namely, for eachload balancer, discovery application 800 may parse the LB pool thereofto identify IP addresses among which the load balancer distributesnetwork traffic. When an IP in the LB pool matches an IP of one of thediscovered virtual computing devices, that virtual computing device maybe mapped to the load balancer. This mapping may be indicated directlyby a connection between the load balancer and the virtual computingdevice, or indirectly by a connection between the LB pool of the loadbalancer and the virtual computing device.

In the case of storage volumes, a relationship between the virtualcomputing devices and the storage volumes may be indicated by theattributes of the virtual computing device. However, the output receivedat arrow 830 may provide additional information regarding the storagevolumes and the endpoints provided thereby. For example, the attributesof the virtual computing devices may indicate the endpoints used by thevirtual computing devices, but not the storage volume itself, or viceversa. The output at arrow 830 may indicate how the endpoints relate tothe storage volumes, thus allowing for a more complete representation ofthe relationships between virtual machines and storage volumes.

Based on or in response to generating the mapping at block 832,discovery application 800 may be configured to request storage of themapping in CMDB 802, as indicated by arrow 834. Based on or in responseto reception of the request at arrow 834, CMDB 802 may be configured tostore the mapping, as indicated by block 836. The mapping may beretrievable by other computing devices to allow for visualization of themapping and thus the service infrastructure provided by remote computingsystem 804.

In some implementations, discovery application 800 may be configured todiscover additional computing resources within remote computing system804. For example, discovery application 800 may be configured todiscover any of the remaining aspects of the model of FIG. 7. Suchdiscovery may be similar to the operations of block 822 through 832.That is, discovery application may, based on the attributes associatedwith the discovered virtual computing devices, identify other computingresources utilized by the virtual computing devices. Discoveryapplication 800 may then query API functions provided by API server 806to obtain attributes of these other computing devices, and, basedthereon, map these other computing devices to the virtual computingdevice, the load balancers, and the storage volumes, among otherpossibilities.

For example, discovery application 800 may be configured to determine,for each geographic region undergoing discovery, two or moreavailability zones in that region among which the virtual computingdevices are distributed. Discovery application 800 may be configured toassociate each virtual computing device with its correspondingavailability zone and reflect this relationship in the generatedmapping. In one example, the attributes of each virtual computing devicemay directly indicate the availability zone in which the virtualcomputing device is hosted. Alternatively, discovery application 800 mayalso identify the subnets assigned to each availability zone. Based onthe IP addresses associated with the subnets and the IP addressesassigned to each of the virtual computing devices, each computing devicemay be related or mapped to a corresponding subnet and thus acorresponding availability zone.

Determining the mapping between availability zones and the virtualcomputing devices also allows each load balancer to be classified as anin-zone load balancer or a cross-zone load balancer. Namely, a loadbalancer (e.g., load balancer 620) that is configured to distributetraffic among virtual computing devices that are distributed between twoor more availability zones may be considered a cross-zone load balancer.Alternatively, a load balancer (e.g., load balancer 640) that isconfigured to distribute traffic among virtual computing devices each ofwhich are found in the same availability zone may be considered anin-zone load balancer. Such load balancer classifications andrelationships with the availability zones may similarly be mapped andstored in CMDB 802 as configuration items.

Discover application 800 may be configured to update the determinedmapping according to a discovery schedule. In one example, discoveryapplication may be configured to periodically (e.g., weekly, daily,every 12 hours, etc.) re-execute the operations of FIG. 8 in order togenerate a revised or updated map indicative of any modification takingplace since the last mapping.

Additionally or alternatively, discovery application 800 may beconfigured to re-execute at least a portion of these operations based onnotifications received from remote computing system 804. Remotecomputing system 804 may be configured to transmit, to a URL associatedwith discovery application 800, notifications of any changes,modifications, or adjustments made of the computing resources therein.Based on such notifications, discovery application 800 may be configuredto select and execute a particular discovery pattern (e.g., a subset ofthe operations discussed above) to obtain updated information regardingthe computing resource that has been modified. Discovery application 800may thus obtain updated attributes that indicate any modifications tothe computing resources and reflect such modifications in CMDB 802 byrevising the mapping. As a result, discovery application 800 may be ableto maintain a near-real-time representation of the computing resourcesprovided by remote computing system 804 and any modifications madethereto.

IX. EXAMPLE RESOURCE ALLOCATION MANAGEMENT FOR REMOTE COMPUTING SYSTEM

Once a mapping of the computing resources in remote computing system 804is determined, the mapping may be used to assist with carrying outvarious other operations in connection with remote computing system 804.For example, based on the number and type of computing resourcesindicated by the map, discovery application 800 may be configured todetermine a cost (e.g., per unit time, total to date, etc.) ofprovisioning the computing resources indicated by the map. Most notably,however, discovery application may be configured to use this mapping tomodify, change, and/or otherwise adjust the discovered computingresources or the attributes thereof. FIGS. 9A, 9B, 9C, and 9D illustraterespective message diagram of operations involved in modifying aspectsof remote computing system 804 by way of discovery application 800.

Namely, discovery application 800 may obtain instructions to modify acomputing resource of remote computing system 804, as indicated by block900. In some implementations, the instructions may be user instructionsreceived by way of a graphical user interface provided by discoveryapplication 800. For example, discovery application 800 may display agraphical representation of the mapping determined by way of theoperations of FIG. 8. A user may interact with the graphicalrepresentation of the mapping (e.g., by clicking, dragging, typing, orotherwise providing input) to add a new computing resource to themapping, remove a computing resource from the mapping, and/or modifyattributes of existing computing resources, among other possibilities.Thus, the graphical user interface may be used to indicate a targetstate of the mapping requested by the user.

In another example, discovery application 800 may be configured toreceive the instructions from a computing device or software applicationexecuting within managed network 300. For example, the softwareapplication may request additional computing resources or request accessto existing computing resources, among other possibilities. In a furtherexample, discovery application 800 may be configured to generate theinstructions without external input. For example, discovery application800 may be configured to maintain the amount of computing resourceswithin a quota or other threshold. The quota or threshold may beselected such that, for example, a cost of the computing resources doesnot exceed a threshold cost (e.g., cost per unit time, total monthlybudget, etc.). Discovery application 800 may additionally oralternatively be configured to request allocation of additionalcomputing resources when utilization of the cloud-based computingenvironment or portion thereof rises above a first threshold, and/orrequest termination of some computing resources when the utilizationfalls below a second threshold. Other reasons for modifying thecomputing resources are possible.

Based on or in response to obtaining the instructions at block 900,discovery application 800 may be configured to generate a first requestto modify the computing resources, as indicated by block 902. In oneexample, resource server 808 provided by remote computing system 804 maybe configured to allow discovery application 800 to remotely modify thecomputing resources provided by remote computing system 804.Specifically, resource server 808 may be configured to allow desiredservice infrastructure modifications or states to be specified asprogrammatic code. For example, resource server 808 may be configured touse an infrastructure-as-code language (e.g., HASHICORP CONFIGURATIONLANGUAGE®) and/or an infrastructure-as-code software application (e.g.,TERRAFORM®) to specify and execute the desired modifications.

To that end, discovery application 800 may define a plurality ofinfrastructure-as-code templates, each corresponding to a modificationthat can be requested by way of discovery application 800. Each templatemay include one or more objects (e.g., JSON objects) made up of one ormore key-value pairs. For example, a template used to deploy a virtualcomputing device may include a first object having key-value pairs for(i) the type of virtual computing device to be deployed (e.g.,processing power, amount of memory, etc.), (ii) a name for the virtualcomputing device, and (iii) an identifier of the operating system thatthe virtual computing device is to execute. The keys included in eachtemplate may define the information to be provided to remote computingsystem 804 in order to effectuate a particular modification. At leastsome of the values in each template may be blank, and may be filled outby discovery application 800 based on the instructions received at block900.

Based on the instructions obtained at block 900, discovery application800 may select one or more of these templates to define the desiredmodification using the infrastructure-as-code language. Discoveryapplication 800 may populate the templates specifying the values for anykeys not already associated with a value (and/or overriding the valuesfor some keys). In this way, discovery application 800 may specify thedesired modifications by, for example, providing an identifier of thespecific computing resource sought to be modified, or indicating a newvalue to which a particular attributes of a computing resource is to beadjusted, among other possibilities.

In another example, the computing resources of remote computing system804 may be modifiable by way of a resource management API provided byresource server 808. In such an implementation, generating the firstrequest may include, for example, selecting an API function used tomodify the computing resource specified by the instructions at block900. The first request may thus be an HTTP request that specifies, byway of one or more parameters thereof, the modification indicated by theinstructions at block 900.

Based on or in response to generation of the first request at block 902,discovery application 800 may be configured to transmit, to resourceserver 808, the first request, as indicated by arrow 904. Based on or inresponse to reception of the first request at arrow 904, resource server808 may be configured to modify the computing resource specified by therequest in the manner defined by the first request, as indicated byblock 906.

Based on or in response to modification of the computing resource atblock 906, resource server 808 may be configured to transmit, todiscovery application 800, a first response indicating the modification,as indicate by arrow 908. The amount of information included in thefirst response may vary depending on the particular remote computingsystem. In some cases, the first response may include a confirmationthat the modification has been executed, without providing anyinformation regarding the details of the modification. In other cases,the first response may provide data that details the modification. Forexample, when a new resource is generated, the response may include aname or a unique identifier associated with the new resource. In somecases, the response may also include the values of each of theattributes associated with the new resource. Similarly, when an existingresource is in some way altered (e.g., a value of an attribute thereofis updated), the first response may include an identifier of theresource, the new value of the updated attribute, and/or the values ofall attributes.

Based on or in response to reception of the transmission at arrow 908,discovery application 800 may be configured to select a discoverypattern for the modified computing resource, as indicated by block 920.Based on or in response to selection of the discovery pattern at block910, discovery application 800 may be configured to execute thediscovery pattern to verify that the modification executed by resourceserver 808 matches that of the instructions obtained at block 900, asindicated by block 912.

The selected discovery pattern may include a subset of the operationsillustrated in and discussed with respect to FIG. 8. That is, ratherthan re-discovering and re-mapping all of the computing resourcesprovided by remote computing system 804, the discovery pattern may focuson the computing device that has been modified and/or any computingresources related thereto. The discovery pattern may be configured todiscover and obtain the attributes associated with the modifiedcomputing resource. Thus, discovery application 800 may use thediscovery and mapping process to confirm that the modification to thecomputing resources has been executed as instructed. The discoverypattern may be used to verify that the computing resource has beencreated, continues to exist, or has been deleted. The discovery patternmay be additionally or alternatively used to verify that the computingresource has the attributes defined by the instructions at block 900. Inshort, discovery application 800 may verify that an actual state of theservice infrastructure determined by execution of the discovery patternsmatches a target state of the service infrastructure specified at block900.

Based on or in response to execution of the discovery pattern at block912, discovery application 800 may be configured to transmit, to APIserver 806, a second request for attributes of the modified computingresource, as indicated by arrow 914. Depending on the specific type ofthe modified computing resource, the second request may be addressed toa specific API function configured to provide the attributes of thatcomputing resource.

Alternatively or additionally, the second request and/or additionalrequests may be addressed to functions corresponding to other computingresources that have a relationship with the modified computing resource.For example, when a virtual computing device is modified to (i) stopusing a first storage volume and (ii) instead use a second storagevolume, an API function associated with storage volumes may be used toobtain the attributes associated with the first and second storagevolumes to verify the modification of the virtual computing device.

Based on or in response to reception of the request at arrow 914, APIserver 806 may be configured to execute an API function addressed by thesecond request, as indicated by block 916. Based on or in response toexecution of the API function, API server 806 may be configured totransmit, to discovery application 800, a second response indicating theoutput of the API function, as indicated by arrow 918. Based on or inresponse to reception of the transmission at arrow 918, discoveryapplication 800 may be configured to determine whether the modificationexecuted by resource server 808 at block 906 (and indicated by thesecond response at arrow 918) matches the instructions received at block900, as indicated by block 920.

In one example, determining whether the modification matches theinstructions may involve generating a preview of an updated mapping ofthe computing resources. The preview may represent (i) any unchangedportions of the mapping determined at block 832 and (ii) themodification to the computing device executed at block 906. The previewof the mapping may be displayed by way of a user interface along with aprompt asking a user to confirm whether the preview matches theinstructions obtained at block 900. When the preview of the mappingmatches the user's instructions, the graphical user interface may beused to receive a corresponding confirmation. On the other hand, whenpreview of the mapping does not match (e.g., is in some way differentfrom) the user's instructions, the graphical user interface may be usedto receive an indication to this effect. In some implementations, theuser interface may also be used to indicate any differences between themodification and the instructions, thus allowing the erroneousmodification to be corrected.

In other examples, discovery application 800 may be configured toautomatically determine whether the modification matches theinstructions. For example, discovery application may determine that anew computing resource has not been provisioned, a computing resourcethat was requested to be deleted continues to exist, an attributerequested to be modified remains unchanged, and/or a relationshiprequested to be formed remains unformed, among other possibilities.Discovery application 800 may, for example, determine a differencebetween the preview of the mapping and the original mapping to identifyany modifications that have actually been performed by resource server808. Discovery application 800 may then compare these differences withthe instructions and determine whether each instruction is associatedwith a corresponding one of the differences.

FIG. 9B illustrates example operations that may be carried out bydiscovery application 800 when the modification to the computingresource matches the instructions. Namely, discovery application 800 maybe configured to determine that the modification matches theinstructions, as indicated by block 922. Based on or in response todetermining that the modification matches the instructions at block 922,discovery application 800 may be configured to update the mapping of thecomputing resources in remote computing system 804 to indicate themodification, as indicate by block 924.

Based on or in response to updating the mapping at block 924, discoveryapplication 800 may be configured to request storage of the mapping asupdated in CMDB 802, as indicated by arrow 926. Based on or in responseto reception of the request at arrow 928, CMDB may be configured tostore the mapping as updated. Accordingly, a successful modification tothe computing resource carried out according to the instructions may beconfirmed by being reflected in the mapping and any visualrepresentation thereof.

On the other hand, FIGS. 9C and 9D illustrate operations that may becarried out when the modification to the computing device does not matchthe instructions, as indicated by blocks 930. The modification might notmatch the instructions when, for example, the instructions containtherein an error. In some cases, the error may be a syntactical error(e.g., when the instructions include incorrectly formatted input) or atypographical error (e.g., when the instructions request that attributesof a virtual computing device that does not exist are modified), amongother possible errors. In another example, the modifications might notmatch the instructions when remote computing system 804 is unable toexecute the modification due to one or more rules. The instructions may,for example, request dedication of computing resources that would exceeda quota or other limit (e.g., cost) set by managed network 300 and/orremote computing system 804. Alternatively, the instructions may requestmodifications of rules (e.g., network security rules, storage volumeread/write permissions, etc.) that are not modifiable, for example, dueto the requestor (e.g., user or application providing the instructionsat block 900) lacking sufficient permissions.

Based on or in response to determining that the modification does notmatch the instructions at block 930, discovery application 800 may beconfigured to generate a third request to undo the modification, asillustrated by block 932. For example, the third request may request amodification that is opposite to the modification indicated by the firstrequest at block 902. In some cases, resource server 808 may providespecific functions configured to undo or roll back one or more recentmodifications to the service infrastructure. In such cases, the thirdrequest may invoke this function and specify the modification to beundone or rolled back.

Based on or in response to generating the third request at block 932,discovery application may be configured to transmit the third request toresource server 808, as indicated by arrow 934. Based on or in responseto reception of the request at arrow 934, resource server 808 may beconfigured to undo the modification to the computing resource, asindicated by block 936. Based on or in response to undoing themodification at block 936, resource server 808 may be configured totransmit, to discovery application 800, a third modification indicatingthat the modification has been undone, as indicated by arrow 938. Thethird response may be similar in its content to the first response atarrow 908.

Based on or in response to reception of the third response at arrow 938,discovery application 800 may be configured to obtain alternativeinstructions to modify the computing resource, as indicated by block940. The alternative instructions may be a modified version of theinstruction obtained at block 900. In some implementations, thealternative instructions may be user instructions obtained by way of thegraphical user interface. In other implementations, discoveryapplication 800, or another software application, may be configured togenerate the alternative instructions based on any differences betweenthe target service infrastructure state indicated by the instructions atblock 900 and the actual service infrastructure state determined atblock 920.

Alternatively or additionally, discovery application 800 may beconfigured to generate a revised request to modify the computingresource, as indicated by block 942 of FIG. 9D. In implementations wherethe operations of FIG. 9D are carried out after the initial modificationis undone according to the operations of FIG. 9C, the revised requestmay be generated with the assumption that the service infrastructure isin the state it was in prior to execution of block 906. Alternatively,in implementations where the operations of FIG. 9D are carried outwithout the operations of FIG. 9C, the revised request may be generatedwith the assumption that the service infrastructure is in the state itwas in after execution of block 906. That is, discovery application maytake into account the initial incorrect modification when generating therevised request.

Based on or in response to generation of the revised request at block942, discovery application 800 may be configured to transmit the revisedrequest to resource server 808, as indicated by arrow 944. Based on orin response to reception of the request at arrow 944, resource server808 may be configured to modify the computing resource according to therevised request, as indicated by block 946. Based on or in response tomodification of the computing resource at block 946, resource server 808may be configured to transmit, to discovery application 800, a fourthresponse indicating a revised modification to the computing resource, asindicated by arrow 948.

Based on or in response to reception of the transmission at arrow 948,discovery application 800 may be configured to re-execute the discoverypattern to verify the modification to the computing resource, asindicated by block 950. Based on or in response to re-execution of thediscovery pattern at block 950, discovery application 800 may beconfigured to transmit, to API server 806, a fifth request forattributes of the modified computing resource, as indicated by arrow952. Based on or in response to reception of the transmission at arrow952, API server 806 may be configured to execute the API functionspecified by the fifth request, as indicated by block 954. Based on orin response to execution of the API function at block 954, API server806 may be configured to transmit, to discovery application 800, a fifthresponse indicating an output of the API function, as indicated by arrow956.

Based on or in response to reception of the transmission at arrow 956,discovery application 800 may be configured to determine whether therevised modification matches the instructions (e.g., the instructionsobtained at block 900 or the alternative instruction of block 940), asindicated by block 958. Notably, the operations of block 942 throughblock 958 (including the operations of the arrows therebetween), may beanalogous to the operations of blocks 902 through 920 of FIG. 9A.

X. EXAMPLE OPERATIONS

FIGS. 10 and 11 are flow charts illustrating example embodiments. Theprocesses illustrated by FIGS. 10 and 11 may be carried out by acomputing device, such as computing device 100, and/or a cluster ofcomputing devices, such as server cluster 200. However, the processescan be carried out by other types of devices or device subsystems. Forexample, the processes could be carried out by a portable computer, suchas a laptop or a tablet device.

The embodiments of FIGS. 10 and 11 may be simplified by the removal ofany one or more of the features shown therein. Aspects of theembodiments of FIGS. 10 and 11 may be combined with one another.Further, these embodiments may be combined with features, aspects,and/or implementations of any of the previous figures or otherwisedescribed herein.

Block 1000 involves obtaining, by a discovery application, a serviceidentifier associated with a managed network that allows access to aremote computing system that provides computing resources on behalf ofthe managed network.

Block 1002 involves identifying, by the discovery application, ageographic region of the remote computing system that contains thecomputing resources associated with the service identifier.

Block 1004 involves identifying, by the discovery application and withinthe geographic region, (i) virtual computing devices allocated to themanaged network and (ii) attributes of the virtual computing devices.

Block 1006 involves identifying, by the discovery application and basedon the attributes of the virtual computing devices, (i) one or more loadbalancers configured to distribute network traffic among the virtualcomputing devices and (ii) one or more storage volumes used by thevirtual computing devices.

Block 1008 involves determining, by the discovery application, a mappingbetween the virtual computing devices, the one or more load balancers,and the one or more storage volumes to represent a serviceinfrastructure of the remote computing system dedicated to the managednetwork.

Block 1010 involves storing, in persistent storage configured to storedata on behalf of the managed network, the mapping as one or moreconfiguration items.

In some embodiments, the discovery application may be configured toidentify, within the geographic region, two or more availability zonesamong which the virtual computing devices are distributed. Each of thetwo or more availability zones may have a different physical locationwithin the geographic region. The discovery application may also beconfigured to determine a distribution of the virtual computing devicesamong the two or more availability zones. The discovery application mayadditionally be configured to update the mapping to indicate thedistribution of the virtual computing devices among the two or moreavailability zones and store, in the persistent storage, the mapping asupdated.

In some embodiments, determining the distribution of the virtualcomputing devices among the two or more availability zones may involvedetermining attributes of a network that (i) includes therein the two ormore availability zones and (ii) is assigned to the managed network.Based on the attributes of the network and for each respectiveavailability zone of the two or more availability zones, a subnet of thenetwork may be identified that is assigned to the respectiveavailability zone. The distribution may be determined based on (i) thesubnet assigned to the respective availability zone and (ii) theattributes of the virtual computing devices.

In some embodiments, identifying the one or more load balancersconfigured to distribute network traffic among the virtual computingdevices may involve identifying a first load balancer of the one or moreload balancers that is configured to distribute traffic among a group oftwo or more of the virtual computing devices. The two or more virtualcomputing devices of the group may be distributed among multipleavailability zones of the two or more availability zones. The mappingbetween the virtual computing devices and the one or more load balancersmay be updated to indicate therein a relationship between the first loadbalancer and the group. The mapping as updated may be stored in thepersistent storage.

In some embodiments, identifying the one or more load balancersconfigured to distribute network traffic among the virtual computingdevices may involve identifying a first load balancer of the one or moreload balancers that is configured to distribute traffic among a group oftwo or more of the virtual computing devices that are each disposed in asingle availability zone of the two or more availability zones. Themapping between the virtual computing devices and the one or more loadbalancers may be updated to indicate therein a relationship between thefirst load balancer and the group. The mapping as updated may be storedin the persistent storage.

In some embodiments, identifying the virtual computing devices mayinvolve identifying the virtual computing devices across multiplegeographic regions. Additionally, identifying the two or moreavailability zones in the geographic region may involve determining, foreach respective virtual computing device of the virtual computingdevices and based on the attributes of the respective virtual computingdevice, a corresponding availability zone within which the respectivevirtual computing device is hosted. For each respective availabilityzone of the corresponding availability zones, a corresponding geographicregion of the multiple geographic regions to which the respectiveavailability zone belongs may be determined based on a predeterminedmapping between the multiple geographic regions and the availabilityzones.

In some embodiments, identifying the virtual computing devices and theattributes of the virtual computing devices may involve generating andtransmitting an HTTP request addressed to a first function of an APIprovided by the remote computing system. The request may specify thegeographic region within which the first function is to identify thevirtual computing devices and the attributes thereof. A response may bereceived from the API that contains (i) an identifier of each respectivevirtual computing device of the virtual computing devices and (ii) foreach respective virtual computing device, the attributes comprising aplurality of URLs. Each respective URL of the plurality of URLs mayaddress a corresponding function of the API configured to identify aspecific type of computing resource associated with the respectivevirtual computing device.

In some embodiments, identifying (i) the one or more load balancers and(ii) the one or more storage volumes may involve selecting, from theplurality of URLs for each respective virtual computing device in theresponse, at least one URL that addresses a second function of the APIconfigured to identify at least one of (i) the one or more loadbalancers or (ii) the one or more storage volumes. Based on the at leastone URL, a second HTTP request addressed to the second function of theAPI may be generated and transmitted. A second response containing oneor more identifiers of the at least one of (i) the one or more loadbalancers or (ii) the one or more storage volumes may be received fromthe API.

In some embodiments, the discovery application may be configured toobtain, from the remote computing system, an indication of costs ofprovisioning different types of the computing resources. The discoveryapplication may also be configured to, based on (i) the indication ofthe costs and (ii) the mapping, determining a total cost associated withthe computing resources provided on behalf of the managed network.

In some embodiments, identifying the attributes of the virtual computingdevices may involve determining, for each respective virtual computingdevice of the virtual computing devices, attributes of a physicalcomputing device on which the respective virtual computing device isexecuted.

In some embodiments, the attributes of the virtual computing devices mayinclude identifiers of the one or more storage volumes. Identifying theone or more storage volumes may involve obtaining, from the remotecomputing system, data that defines attributes of a plurality of storagevolumes. Based on the identifiers of the one or more storage volumes, asubset of the data that defines the attributes of the one or morestorage volumes may be selected. The mapping may indicate the attributesof the one or more storage volumes.

In some embodiments, the attributes of the virtual computing devices mayinclude IP addresses of the virtual computing devices. Identifying theone or more load balancers may involve obtaining, from the remotecomputing system, data that identifies a plurality of load balancerswithin the remote computing system. Based on the data and for eachrespective load balancer of the plurality of load balancers, a group ofIP addresses may be determined among which the respective load balanceris configured to distribute network traffic. For each respective virtualcomputing device of the virtual computing devices, a corresponding loadbalancer of the plurality of load balancers may be identified such thatthe group of IP addresses of the corresponding load balancer includesthe IP address of the respective virtual computing device.

In some embodiments, the remote computing system may be configured totransmit, to a URL that addresses the discovery application,notifications of modifications to the computing resources. The discoveryapplication may be configured to receive, from the remote computingsystem, a notification that a particular computing resource has beenmodified. In response to receiving the notification, the discoveryapplication may obtain, from the remote computing system, data thatidentifies a modification to the particular computing resource. Thediscovery application may also be configured to update the mapping basedon the data to indicate the modification to the particular computingresource and store, in the persistent storage, the mapping as updated.

In some embodiments, the modification to the particular computingresource may include at least one of (i) creation of the particularcomputing resource, (ii) deletion of the particular computing resource,or (iii) modification of one or more attributes of the particularcomputing resource. The particular computing resource may include atleast one of the virtual computing devices, the one or more loadbalancers, or the one or more storage volumes.

In some embodiments, identifying the one or more storage volumes mayinvolve identifying a plurality of data storage interfaces by way ofwhich the one or more storage volumes are accessible by the virtualcomputing devices. Determining the mapping between the virtual computingdevices and the one or more storage volumes may involve determining, foreach respective storage volume of the one or more storage volumes, oneor more data storage interfaces by way of which the respective storagevolume is accessible by a corresponding virtual computing device of thevirtual computing devices.

In some embodiments, the attributes may indicate, for each respectivevirtual computing device of the virtual computing devices, acorresponding operating system image from which the respective virtualcomputing device is provisioned. The mapping may indicate thecorresponding operating system image for each respective virtualcomputing device.

In some embodiments, the persistent storage may be disposed within aremote network management platform (e.g., in a computational instancethereof).

Turning now to FIG. 11, block 1100 involves obtaining, by a discoveryapplication, instructions to modify a computing resource of computingresources provided by a remote computing system to a managed network. Amapping of the computing resources may be stored as one or moreconfiguration items in persistent storage on behalf of the managednetwork. The mapping may represent a service infrastructure of theremote computing system dedicated to the managed network.

Block 1102 involves, based on the instructions, generating andtransmitting, by the discovery application and to the remote computingsystem, a request to modify the computing resource.

Block 1104 involves receiving, by the discovery application and from theremote computing system, a response indicating a modification to thecomputing resource.

Block 1106 involves selecting, by the discovery application, a discoverypattern configured to verify the modification to the computing resourceby obtaining attributes associated therewith.

Block 1108 involves obtaining, by the discovery application and from theremote computing system, the attributes associated with the computingresource by executing the discovery pattern.

Block 1110 involves determining, by the discovery application and basedon the attributes associated with the computing resource, that themodification to the computing resource has been completed according tothe instructions.

Block 1112 involves, based on the modification to the computing resourcehaving been completed according to the instructions, updating, by thediscovery application, the mapping to indicate the modification.

Block 1114 involves storing, in the persistent storage, the mapping asupdated.

In some embodiments, the discovery application may also be configured toobtain second instructions to modify a second computing resourceprovided by the remote computing system and, based on the secondinstructions, generate and transmit, to the remote computing system, asecond request to modify the second computing resource. The discoveryapplication may receive, from the remote computing system, a secondresponse indicating a second modification to the second computingresource and select a second discovery pattern configured to verify thesecond modification to the second computing resource by obtaining secondattributes associated therewith. The discovery application may alsoobtain, from the remote computing system, the second attributesassociated with the second computing resource by executing the seconddiscovery pattern. The discovery application may additionally determine,based on the second attributes associated with the second computingresource, that the second modification to the second computing resourcehas not been completed according to the second instructions.

In some embodiments, the discovery application may be configured to,based on the second modification to the second computing resource nothaving been completed according to the second instructions (i) generateand transmit, to the remote computing system, a third request to modifythe second computing resource, where the third request is a revisedversion of the second request, (ii) receive, from the remote computingsystem, a third response indicating a third modification to the secondcomputing resource, (iii) obtain, from the remote computing system andby re-executing the second discovery pattern, updated second attributesassociated with the second computing resource, (iv) determine, based onthe updated second attributes, that the third modification to the secondcomputing resource has been completed according to the secondinstructions, and (v) based on the third modification to the computingresource having been completed according to the second instructions,update the mapping to indicate the third modification and store, in thepersistent storage, the second mapping as updated.

In some embodiments, the discovery application may, based on the secondmodification to the second computing resource not having been completedaccording to the second instructions, (i) generate and transmit, to theremote computing system, a third request to undo the second modificationto the second computing resource, and (ii) verify that the secondmodification has been undone by re-executing the second discoverypattern.

In some embodiments, obtaining the instructions to modify the computingresource may involve displaying, by way of a graphical user interface, agraphical representation of the mapping and receiving, by way of thegraphical user interface, input indicating a target state of thegraphical representation to be achieved by the modification. Based onthe input, the discovery application may determine (i) the computingresource to modify and (ii) a manner in which the computing resource isto be modified to achieve the target state of the graphicalrepresentation.

In some embodiments, generating the request to modify the computingresource may involve selecting, from a plurality of templates thatdefine, as programmatic code, a plurality of candidate modifications tothe computing resources provided to the managed network, a particulartemplate that defines the modification to the computing resourceindicated by the instructions. The particular template may be populatedaccording to the instructions.

In some embodiments, generating the request to modify the computingresource may involve generating an HTTP request addressed to a functionof an API provided by the remote computing system. The function of theAPI may be configured to manage the computing resources provided to themanaged network. The request may specify the computing resource and themodification thereto as one or more HTTP parameters.

In some embodiments, the HTTP parameters may include at least one of:(i) a URL resource path parameter that identifies a specific resourceprovided by a server device that hosts the API, (ii) a URL queryparameter comprising a key and value pair, (iii) an HTTP headerparameter, (iv) an HTTP cookie parameter, or (v) an HTTP body parameter.

In some embodiments, the computing resource may be a virtual computingdevice. The modification to the virtual computing device may include atleast one of: (i) provisioning of the virtual computing device, (ii)deprovisioning of the virtual computing device, (iii) suspendingoperation of the virtual computing device, (iv) changing an amount ofprocessor resources available to the virtual computing device, or (v)changing an amount of memory available to the virtual computing device.

In some embodiments, the computing resource may be a storage volume. Themodification to the storage volume may include at least one of: (i)provisioning of the storage volume, (ii) deprovisioning of the storagevolume, (iii) creating a snapshot of the storage volume, (iv) restoringthe storage volume from a snapshot, or (v) changing a size of thestorage volume.

In some embodiments, selecting the discovery pattern may involvedetermining a type of the computing resource based on at least one of:(i) the instructions, (ii) the request, or (iii) the response. Thediscovery pattern may be selected that is configured to obtainattributes associated with the type of the computing resource.

In some embodiments, the instructions to modify the computing resourcemay indicate one or more target relationships between the computingresource and one or more other computing resources provided to themanaged network by the remote computing system. Determining that themodification to the computing resource has been completed according tothe instructions may involve determining, based on the attributesassociated with the computing resource, one or more actual relationshipsbetween the computing resource and the one or more other computingresources and determining that the one or more actual relationshipsmatch the one or more target relationships.

In some embodiments, the instructions to modify the computing resourcemay indicate one or more target relationships between the computingresource and one or more other computing resources provided to themanaged network by the remote computing system. Selecting the discoverypattern may involve selecting, for each respective computing resource ofthe one or more other computing resources, a corresponding discoverypattern configured to obtain additional attributes associated with therespective computing resource. The discovery application may obtain,from the remote computing system and for each respective computingresource, the additional attributes associated with the respectivecomputing resource by executing the corresponding discovery pattern.

In some embodiments, determining that the modification to the computingresource has been completed according to the instructions may involvedetermining, based on the additional attributes associated with eachrespective computing resource of the one or more other computingresources, one or more actual relationships between the computingresource and the one or more other computing resources and determiningthat the one or more actual relationships match the one or more targetrelationships.

In some embodiments, determining that the modification to the computingresource has been completed according to the instructions may involvegenerating a preview of the mapping as updated to indicate themodification, displaying, by way of a graphical user interface, thepreview of the mapping as updated, and receiving, by way of thegraphical user interface, input indicating that the preview of themapping represents the modification as indicated by the instructions.

XI. CONCLUSION

The present disclosure is not to be limited in terms of the particularembodiments described in this application, which are intended asillustrations of various aspects. Many modifications and variations canbe made without departing from its scope, as will be apparent to thoseskilled in the art. Functionally equivalent methods and apparatuseswithin the scope of the disclosure, in addition to those describedherein, will be apparent to those skilled in the art from the foregoingdescriptions. Such modifications and variations are intended to fallwithin the scope of the appended claims.

The above detailed description describes various features and operationsof the disclosed systems, devices, and methods with reference to theaccompanying figures. The example embodiments described herein and inthe figures are not meant to be limiting. Other embodiments can beutilized, and other changes can be made, without departing from thescope of the subject matter presented herein. It will be readilyunderstood that the aspects of the present disclosure, as generallydescribed herein, and illustrated in the figures, can be arranged,substituted, combined, separated, and designed in a wide variety ofdifferent configurations.

With respect to any or all of the message flow diagrams, scenarios, andflow charts in the figures and as discussed herein, each step, block,and/or communication can represent a processing of information and/or atransmission of information in accordance with example embodiments.Alternative embodiments are included within the scope of these exampleembodiments. In these alternative embodiments, for example, operationsdescribed as steps, blocks, transmissions, communications, requests,responses, and/or messages can be executed out of order from that shownor discussed, including substantially concurrently or in reverse order,depending on the functionality involved. Further, more or fewer blocksand/or operations can be used with any of the message flow diagrams,scenarios, and flow charts discussed herein, and these message flowdiagrams, scenarios, and flow charts can be combined with one another,in part or in whole.

A step or block that represents a processing of information cancorrespond to circuitry that can be configured to perform the specificlogical functions of a herein-described method or technique.Alternatively or additionally, a step or block that represents aprocessing of information can correspond to a module, a segment, or aportion of program code (including related data). The program code caninclude one or more instructions executable by a processor forimplementing specific logical operations or actions in the method ortechnique. The program code and/or related data can be stored on anytype of computer readable medium such as a storage device including RAM,a disk drive, a solid state drive, or another storage medium.

The computer readable medium can also include non-transitory computerreadable media such as computer readable media that store data for shortperiods of time like register memory and processor cache. The computerreadable media can further include non-transitory computer readablemedia that store program code and/or data for longer periods of time.Thus, the computer readable media may include secondary or persistentlong term storage, like ROM, optical or magnetic disks, solid statedrives, compact-disc read only memory (CD-ROM), for example. Thecomputer readable media can also be any other volatile or non-volatilestorage systems. A computer readable medium can be considered a computerreadable storage medium, for example, or a tangible storage device.

Moreover, a step or block that represents one or more informationtransmissions can correspond to information transmissions betweensoftware and/or hardware modules in the same physical device. However,other information transmissions can be between software modules and/orhardware modules in different physical devices.

The particular arrangements shown in the figures should not be viewed aslimiting. It should be understood that other embodiments can includemore or less of each element shown in a given figure. Further, some ofthe illustrated elements can be combined or omitted. Yet further, anexample embodiment can include elements that are not illustrated in thefigures.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purpose ofillustration and are not intended to be limiting, with the true scopebeing indicated by the following claims.

What is claimed is:
 1. A computing system comprising: persistent storageconfigured to store, as one or more configuration items and on behalf ofa managed network, a mapping of computing resources provided by a remotecomputing system to the managed network, wherein the mapping representsa service infrastructure of the remote computing system dedicated to themanaged network; and a discovery application configured to performoperations comprising: obtaining instructions to modify a computingresource provided by the remote computing system; based on theinstructions, generating and transmitting, to the remote computingsystem, a request to modify the computing resource; receiving, from theremote computing system, a response indicating a modification to thecomputing resource; selecting a discovery pattern configured to verifythe modification to the computing resource by obtaining attributesassociated therewith; obtaining, from the remote computing system, theattributes associated with the computing resource by executing thediscovery pattern; determining, based on the attributes associated withthe computing resource, that the modification to the computing resourcehas been completed according to the instructions; based on themodification to the computing resource having been completed accordingto the instructions, updating the mapping to indicate the modification;and storing, in the persistent storage, the mapping as updated.
 2. Thecomputing system of claim 1, wherein the operations further comprise:obtaining second instructions to modify a second computing resourceprovided by the remote computing system; based on the secondinstructions, generating and transmitting, to the remote computingsystem, a second request to modify the second computing resource;receiving, from the remote computing system, a second responseindicating a second modification to the second computing resource;selecting a second discovery pattern configured to verify the secondmodification to the second computing resource by obtaining secondattributes associated therewith; obtaining, from the remote computingsystem, the second attributes associated with the second computingresource by executing the second discovery pattern; and determining,based on the second attributes associated with the second computingresource, that the second modification to the second computing resourcehas not been completed according to the second instructions.
 3. Thecomputing system of claim 2, wherein the operations further comprise:based on the second modification to the second computing resource nothaving been completed according to the second instructions: (i)generating and transmitting, to the remote computing system, a thirdrequest to modify the second computing resource, wherein the thirdrequest is a revised version of the second request, (ii) receiving, fromthe remote computing system, a third response indicating a thirdmodification to the second computing resource, (iii) obtaining, from theremote computing system and by re-executing the second discoverypattern, updated second attributes associated with the second computingresource, (iv) determining, based on the updated second attributes, thatthe third modification to the second computing resource has beencompleted according to the second instructions, and (v) based on thethird modification to the computing resource having been completedaccording to the second instructions, updating the mapping to indicatethe third modification and storing, in the persistent storage, thesecond mapping as updated.
 4. The computing system of claim 2, whereinthe operations further comprise: based on the second modification to thesecond computing resource not having been completed according to thesecond instructions: (i) generating and transmitting, to the remotecomputing system, a third request to undo the second modification to thesecond computing resource, and (ii) verifying that the secondmodification has been undone by re-executing the second discoverypattern.
 5. The computing system of claim 1, wherein obtaining theinstructions to modify the computing resource comprises: displaying, byway of a graphical user interface, a graphical representation of themapping; receiving, by way of the graphical user interface, inputindicating a target state of the graphical representation to be achievedby the modification; and determining, based on the input, (i) thecomputing resource to modify and (ii) a manner in which the computingresource is to be modified to achieve the target state of the graphicalrepresentation.
 6. The computing system of claim 1, wherein generatingthe request to modify the computing resource comprises: selecting, froma plurality of templates that define, as programmatic code, a pluralityof candidate modifications to the computing resources provided to themanaged network, a particular template that defines the modification tothe computing resource indicated by the instructions; and populating theparticular template according to the instructions.
 7. The computingsystem of claim 1, wherein generating the request to modify thecomputing resource comprises: generating a hypertext transfer protocol(HTTP) request addressed to a function of an application programminginterface (API) provided by the remote computing system, wherein thefunction of the API is configured to manage the computing resourcesprovided to the managed network, and wherein the request specifies thecomputing resource and the modification thereto as one or more HTTPparameters.
 8. The computing system of claim 7, wherein the HTTPparameters comprise at least one of: (i) a URL resource path parameterthat identifies a specific resource provided by a server device thathosts the API, (ii) a URL query parameter comprising a key and valuepair, (iii) an HTTP header parameter, (iv) an HTTP cookie parameter, or(v) an HTTP body parameter.
 9. The computing system of claim 1, whereinthe computing resource comprises a virtual computing device, and whereinthe modification to the virtual computing device comprises at least oneof: (i) provisioning of the virtual computing device, (ii)deprovisioning of the virtual computing device, (iii) suspendingoperation of the virtual computing device, (iv) changing an amount ofprocessor resources available to the virtual computing device, or (v)changing an amount of memory available to the virtual computing device.10. The computing system of claim 1, wherein the computing resourcecomprises a storage volume, and wherein the modification to the storagevolume comprises at least one of: (i) provisioning of the storagevolume, (ii) deprovisioning of the storage volume, (iii) creating asnapshot of the storage volume, (iv) restoring the storage volume from asnapshot, or (v) changing a size of the storage volume.
 11. Thecomputing system of claim 1, wherein selecting the discovery patterncomprises: determining a type of the computing resource based on atleast one of: (i) the instructions, (ii) the request, or (iii) theresponse; and selecting the discovery pattern that is configured toobtain attributes associated with the type of the computing resource.12. The computing system of claim 1, wherein the instructions to modifythe computing resource indicate one or more target relationships betweenthe computing resource and one or more other computing resourcesprovided to the managed network by the remote computing system, andwherein determining that the modification to the computing resource hasbeen completed according to the instructions comprises: determining,based on the attributes associated with the computing resource, one ormore actual relationships between the computing resource and the one ormore other computing resources; and determining that the one or moreactual relationships match the one or more target relationships.
 13. Thecomputing system of claim 1, wherein the instructions to modify thecomputing resource indicate one or more target relationships between thecomputing resource and one or more other computing resources provided tothe managed network by the remote computing system, wherein selectingthe discovery pattern comprises selecting, for each respective computingresource of the one or more other computing resources, a correspondingdiscovery pattern configured to obtain additional attributes associatedwith the respective computing resource, and wherein the operationsfurther comprise: obtaining, from the remote computing system and foreach respective computing resource, the additional attributes associatedwith the respective computing resource by executing the correspondingdiscovery pattern.
 14. The computing system of claim 13, whereindetermining that the modification to the computing resource has beencompleted according to the instructions comprises: determining, based onthe additional attributes associated with each respective computingresource of the one or more other computing resources, one or moreactual relationships between the computing resource and the one or moreother computing resources; and determining that the one or more actualrelationships match the one or more target relationships.
 15. Thecomputing system of claim 1, wherein determining that the modificationto the computing resource has been completed according to theinstructions comprises: generating a preview of the mapping as updatedto indicate the modification; displaying, by way of a graphical userinterface, the preview of the mapping as updated; and receiving, by wayof the graphical user interface, input indicating that the preview ofthe mapping represents the modification as indicated by theinstructions.
 16. A computer-implemented method comprising: obtaining,by a discovery application, instructions to modify a computing resourceof computing resources provided by a remote computing system to amanaged network, wherein a mapping of the computing resources is storedas one or more configuration items in persistent storage on behalf ofthe managed network, and wherein the mapping represents a serviceinfrastructure of the remote computing system dedicated to the managednetwork; based on the instructions, generating and transmitting, by thediscovery application and to the remote computing system, a request tomodify the computing resource; receiving, by the discovery applicationand from the remote computing system, a response indicating amodification to the computing resource; selecting, by the discoveryapplication, a discovery pattern configured to verify the modificationto the computing resource by obtaining attributes associated therewith;obtaining, by the discovery application and from the remote computingsystem, the attributes associated with the computing resource byexecuting the discovery pattern; determining, by the discoveryapplication and based on the attributes associated with the computingresource, that the modification to the computing resource has beencompleted according to the instructions; based on the modification tothe computing resource having been completed according to theinstructions, updating, by the discovery application, the mapping toindicate the modification; and storing, in the persistent storage, themapping as updated.
 17. The computer-implemented method of claim 16,wherein obtaining the instructions to modify the computing resourcecomprises: displaying, by way of a graphical user interface, a graphicalrepresentation of the mapping; receiving, by way of the graphical userinterface, input indicating a target state of the graphicalrepresentation to be achieved by the modification; and determining,based on the input, (i) the computing resource to modify and (ii) amanner in which the computing resource is to be modified to achieve thetarget state of the graphical representation.
 18. Thecomputer-implemented method of claim 16, wherein the instructions tomodify the computing resource indicate one or more target relationshipsbetween the computing resource and one or more other computing resourcesprovided to the managed network by the remote computing system, whereinselecting the discovery pattern comprises selecting, for each respectivecomputing resource of the one or more other computing resources, acorresponding discovery pattern configured to obtain additionalattributes associated with the respective computing resource, andwherein the method further comprises: obtaining, from the remotecomputing system and for each respective computing resource, theadditional attributes associated with the respective computing resourceby executing the corresponding discovery pattern.
 19. Thecomputer-implemented method of claim 18, wherein determining that themodification to the computing resource has been completed according tothe instructions comprises: determining, based on the additionalattributes associated with each respective computing resource of the oneor more other computing resources, one or more actual relationshipsbetween the computing resource and the one or more other computingresources; and determining that the one or more actual relationshipsmatch the one or more target relationships.
 20. An article ofmanufacture including a non-transitory computer-readable medium, havingstored thereon program instructions that, upon execution by a computingsystem, cause the computing system to perform operations comprising:obtaining instructions to modify a computing resource of computingresources provided by a remote computing system to a managed network,wherein a mapping of the computing resources is stored as one or moreconfiguration items in persistent storage on behalf of the managednetwork, and wherein the mapping represents a service infrastructure ofthe remote computing system dedicated to the managed network; based onthe instructions, generating and transmitting, to the remote computingsystem, a request to modify the computing resource; receiving, from theremote computing system, a response indicating a modification to thecomputing resource; selecting a discovery pattern configured to verifythe modification to the computing resource by obtaining attributesassociated therewith; obtaining, from the remote computing system, theattributes associated with the computing resource by executing thediscovery pattern; determining, based on the attributes associated withthe computing resource, that the modification to the computing resourcehas been completed according to the instructions; based on themodification to the computing resource having been completed accordingto the instructions, updating the mapping to indicate the modification;and storing, in the persistent storage, the mapping as updated.